Schladt, T. ; Engelmann, N. ; Kubaczka, E. ; Hochberger, C. ; Koeppl, H. (2021):
Automated Design of Robust Genetic Circuits: Structural Variants and Parameter Uncertainty.
In: ACS Synthetic Biology, (Early Access), ACS Publications, ISSN 2161-5063,
DOI: 10.1021/acssynbio.1c00193,
[Article]

Prangemeier, T. ; Wildner, C. ; Françani, A. ; Reich, C. ; Koeppl, H. (2021):
Yeast cell segmentation in microstructured environments with deep learning.
In: Biosystems, Elsevier, ISSN 0303-2647,
DOI: 10.1016/j.biosystems.2021.104557,
[Article]

Köhs, L. ; Alt, B. ; Koeppl, H. (2021):
Variational Inference for Continuous-Time Switching Dynamical Systems.
35th Conference on Neural Information Processing Systems, virtual Conference, 06.-14.12.2021, [Conference or Workshop Item]

Prangemeier, T. ; Reich, C. ; Wildner, C. ; Koeppl, H. (2021):
Multi-StyleGAN: Towards Image-Based Simulation of Time-Lapse Live-Cell Microscopy.
In: LNCS, 12908, In: Medical Image Computing and Computer Assisted Intervention - MICCAI 2021, pp. 476-486,
Springer, 24th International Conference on Medical Image Computing and Computer-Assisted Intervention, Strasbourg, France, 27.09.-01.10.2021, ISBN 978-3-030-87236-6,
DOI: 10.1007/978-3-030-87237-3_46,
[Conference or Workshop Item]

Kruk, N. ; Carrillo, J.A. ; Koeppl, H. (2021):
A Finite Volume Method for Continuum Limit Equations of Nonlocally Interacting Active Chiral Particles.
In: Journal of Computational Physics, 440, Elsevier, ISSN 0021-9991,
DOI: 10.1016/j.jcp.2021.110275,
[Article]

Schladt, T. ; Engelmann, N. ; Kubaczka, E. ; Hochberger, C. ; Koeppl, H. (2021):
Automated Design of Robust Genetic Circuits: Structural Variants and Parameter Uncertainty.
In: biorxiv, 2021 (Preprint), Cold Spring Harbor Laboratory, DOI: 10.1101/2021.08.13.456094,
[Article]

Linzner, D. ; Koeppl, H. (2021):
Active Learning of Continuous-time Bayesian Networks through Interventions.
In: Proceedings of the 38th International Conference on Machine Learning,
ML Research Press, 38th International Conference on Machine Learning, virtual Conference, 18.-24.07.2021, ISSN 2640-3498,
[Conference or Workshop Item]

Ion, Ion Gabriel ; Wildner, C. ; Loukrezis, D. ; Koeppl, H. ; De Gersem, H. (2021):
Tensor-train approximation of the chemical master equation and its application for parameter inference.
In: The Journal of Chemical Physics, 155 (034102), ISSN 0021-9606,
DOI: 10.1063/5.0045521,
[Article]

Kuebert, T. ; Puder, H. ; Koeppl, H. (2021):
Improving Daily Routine Recognition in Hearing Aids Using Sequence Learning.
In: IEEE Access, 9, pp. 93237-93247. IEEE, ISSN 2169-3536,
DOI: 10.1109/ACCESS.2021.3092763,
[Article]

Lehr, F.-X. ; Kuzembayeva, A. ; Bailey, M. ; Kleindienst, W. ; Kabisch, J. ; Koeppl, H. (2021):
Functionalizing cell-free systems with CRISPR-associated proteins: Application to RNA-based circuit engineering.
In: ACS Synthetic Biology, (Preprint), ACS Publications, ISSN 2161-5063,
DOI: 10.1101/2021.04.08.438922,
[Article]

Kuebert, T. ; Puder, H. ; Koeppl, H. (2021):
Daily Routine Recognition for Hearing Aid Personalization.
In: SN Computer Science, 133 (2), pp. 1-12. Springer, e-ISSN 2661-8907,
DOI: 10.1007/s42979-021-00538-3,
[Article]

Ourari, R. ; Cui, K. ; Koeppl, H. (2021):
Decentralized Swarm Collision Avoidance for Quadrotors via End-to-End Reinforcement Learning.
Preprint, arXiv preprint, [Conference or Workshop Item]

Cui, K. ; Tahir, A. ; Sinzger, M. ; Koeppl, H. (2021):
Discrete-Time Mean Field Control with Environment States.
Preprint, 60th Conference on Decision and Control (CDC2021), Austin, USA, 13.-15.12.2021, [Conference or Workshop Item]

Wildner, C. ; Koeppl, H. (2021):
Moment-Based Variational Inference for Stochastic Differential Equations.
24th International Conference on Artificial Intelligence and Statistics (AISTATS), virtual Conference, 13.-15.04.2021, [Conference or Workshop Item]

Reich, C. ; Prangemeier, T. ; Özdemir, C. ; Koeppl, H. (2021):
OSS-Net: Memory Efficient High Resolution Semantic Segmentation of 3D Medical Data.
32nd British Machine Vision Conference, virtual Conference, 22.-25.11.2021, [Conference or Workshop Item]

Prangemeier, Tim ; Reich, C. ; Koeppl, H. (2020):
Attention-Based Transformers for Instance Segmentation of Cells in Microstructures.
IEEE International Conference on Bioinformatics and Biomedicine (IEEE BIBM 2020), virtual Conference, 16.-19.12., [Conference or Workshop Item]

Kruk, N. ; Maistrenko, Y. ; Koeppl, H. (2020):
Solitary states in the mean-field limit.
In: Chaos: An Interdisciplinary Journal of Nonlinear Science, 30 (11), American Institute of Physics, ISSN 1054-1500,
DOI: 10.1063/5.0029585,
[Article]

Alt, B. ; Schultheis, M. ; Koeppl, H. (2020):
POMDPs in Continuous Time and Discrete Spaces.
In: Advances in Neural Information Processing Systems 33 (NeurIPS 2020),
34th Conference on Neural Information Processing Systems, virtual Conference, 06.-12.12.2020, [Conference or Workshop Item]

Kruk, N. ; Carrillo, J.A. ; Koeppl, H. (2020):
Traveling bands, clouds and vortices of chiral active matter.
In: Physical Review E, 102 (2), pp. 022604. American Physical Society, ISSN 2470-0045,
DOI: 10.1103/PhysRevE.102.022604,
[Article]

Yang, S. ; Koeppl, H. (2020):
The Hawkes Edge Partition Model for Continuous-time Event-based Temporal Networks.
pp. 460-469, 36th Conference on Uncertainty in Artificial Intelligence (UAI), virtual Conference, August 03.-06., 2020, ISSN 2640-3498,
[Conference or Workshop Item]

Engelmann, N. ; Linzner, D. ; Koeppl, H. (2020):
Continuous-Time Bayesian Networks with Clocks.
International Conference on Machine Learning 2020, virtual Conference, 12.-18.07., [Conference or Workshop Item]

Sinzger, M. ; Gehri, M. ; Koeppl, H. (2020):
Poisson channel with binary Markov input and average sojourn time constraint.
pp. 2873-2878, ISIT'20 - International Symposium on Information Theory, virtual online conference, 21.-26. June 2020, ISBN 978-1-7281-6433-5,
DOI: 10.1109/ISIT44484.2020.9174360,
[Conference or Workshop Item]

Prangemeier, Tim ; Lehr, F.-X. ; Schoeman, R.M. ; Koeppl, H. (2020):
Microfluidic platforms for the dynamic characterisation of synthetic circuitry.
In: Current Opinion in Biotechnology, 63, pp. 167-176. Elsevier, ISSN 0958-1669,
DOI: 10.1016/j.copbio.2020.02.002,
[Article]

KhudaBukhsh, W. R. ; Kar, S. ; Alt, B. ; Rizk, A. ; Koeppl, H. (2020):
Generalized Cost-Based Job Scheduling in Very Large Heterogenous Cluster Systems.
In: IEEE Transactions on Parallel and Distributed Systems (TPDS), 31 (11), pp. 2594-2604. IEEE, ISSN 1045-9219, e-ISSN 1045-9219,
DOI: 10.1109/TPDS.2020.2997771,
[Article]

Kumar, S. ; Lun, X.-K. ; Bodenmiller, B. ; Rodriguez Martinez, M. ; Koeppl, H. (2020):
Stabilized Reconstruction of Signaling Networks from Single-Cell Cue-Response Data.
In: Scientific reports, 10, p. 1233. Springer Nature, ISSN 2045-2322,
DOI: 10.1038/s41598-019-56444-5,
[Article]

Prangemeier, Tim ; Wildner, C. ; Francani, A. O. ; Reich, C. ; Koeppl, H. (2020):
Multiclass Yeast Segmentation in Microstructured Environments with Deep Learning.
IEEE, International Conference on Computational Intelligence in Bioinformatics and Computational Biology, virtual Conference, October 27-29, 2020, [Conference or Workshop Item]

Altintan, D. ; Koeppl, H. (2019):
Hybrid master equation for jump-diffusion approximation of biomolecular reaction networks.
In: BIT Numerical Mathematics, Springer Nature, Netherlands, ISSN 1572-9125,
DOI: 10.1007/s10543-019-00781-4,
[Article]

KhudaBukhsh, W. R. ; Auddy, A. ; Disser, Y. ; Koeppl, H. (2019):
Approximate Lumpability for Markovian Agent-based Models Using Local Symmetries.
In: Jounal of Applied Probability, 56 (3), pp. 647-671. Cambridge University Press, DOI: 10.1017/jpr.2019.44,
[Article]

Alt, B. ; Šošić, A. ; Koeppl, H. (2019):
Correlation Priors for Reinforcement Learning.
33rd Conference on Neural Information Processing Systems (NeurIPS 2019), Vancouver, Kanada, 09.12.-13.12.2019, [Conference or Workshop Item]

Linzner, D. ; Schmidt, M. ; Koeppl, H. (2019):
Scalable Structure Learning of Continuous-Time Bayesian Networks from Incomplete Data.
33rd Conference on Neural Information Processing Systems (NeurIPS 2019), Vancouver, Canada, 09.-13.12., [Conference or Workshop Item]

KhudaBukhsh, W. R. ; Kar, S. ; Koeppl, H. ; Rizk, A. (2019):
Provisioning and Performance Evaluation of Parallel Systems with Output Synchronization.
In: ACM Transactions on Modeling and Performance Evaluation of Computing Systems (TOMPECS), 4 (1), pp. Art. 6. ISSN 2376-3639,
DOI: 10.1145/3300142,
[Article]

Kang, H.-W. ; KhudaBukhsh, W. R. ; Koeppl, H. ; Rempala, G. A. (2019):
Quasi-steady-state approximations derived from the stochastic model of enzyme kinetics.
In: Bulletin of Mathematical Biology, 81, pp. 1303-1336. Springer, ISSN 0092-8240,
DOI: 10.1007/s11538-019-00574-4,
[Article]

Falk, J. ; Bronstein, L. ; Hanst, M. ; Drossel, B. ; Koeppl, H. (2019):
Context in Synthetic Biology: Memory Effects of Environments with Mono-molecular Reactions.
In: The Journal of Chemical Physics, 150 (2), American Institute of Physics, ISSN 0021-9606,
DOI: 10.1063/1.5053816,
[Article]

Linzner, D. ; Koeppl, H. (2018):
Cluster Variational Approximations for Structure Learning of Continuous-Time Bayesian Networks from Incomplete Data.
32. Conference on Neural Information Processing Systems, Montreal, Canada, December 3-8, 2018, [Conference or Workshop Item]

Yang, S. ; Koeppl, H. (2018):
Collapsed Variational Inference for Nonparametric Bayesian Group Factor Analysis.
IEEE International Conference on Data Mining (ICDM'18), Singapore, 17.-20. November 2018, [Conference or Workshop Item]

Al-Sayed, S. ; Koeppl, H. (2018):
Network Reconstruction from Time-Course Perturbation Data Using Multivariate Gaussian Processes.
In: IEEE International Workshop on Machine Learning for Signal Processing,
IEEE International Workshop on Machine Learning for Signal Processing, Aalborg, Denmark, 17.-20. September 2018, [Conference or Workshop Item]

Sulaimanov, N. ; Koeppl, H. ; Burdet, F. ; Ibberson, M. ; Pagni, M. ; Kumar, S. (2018):
Inferring gene expression networks with hubs using a degree weighted Lasso approach.
In: Bioinformatics (Oxford, England), bty716, Oxford University Press, ISSN 1367-4803,
DOI: 10.1093/bioinformatics/bty716,
[Article]

Kruk, N. ; Koeppl, H. ; Maistrenko, Y. (2018):
Self-propelled Chimeras.
In: Physical Review E, American Physical Society, ISSN 2470-0045,
[Article]

Yang, S. ; Koeppl, H. (2018):
Dependent Relational Gamma Process Models for Longitudinal Networks.
80, In: Proceedings of Machine Learning Research (PMLR), pp. 5547-5556,
Thirty-fifth International Conference on Machine Learning, Stockholm, Denmark, July 10-15, 2018, [Conference or Workshop Item]

Bronstein, L. ; Koeppl, H. (2018):
Marginal process framework: A model reduction tool for Markov jump processes.
In: Physical Review E, 97 (6), American Physical Society, ISSN 2470-0045,
DOI: 10.1103/PhysRevE.97.062147,
[Article]

Šošić, A. ; Zoubir, A. M. ; Koeppl, H. (2018):
A Bayesian Approach to Policy Recognition and State Representation Learning.
In: IEEE Transactions on Pattern Analysis and Machine Intelligence, 40 (6), pp. 1295-1308. DOI: 10.1109/TPAMI.2017.2711024,
[Article]

Šošić, A. ; Zoubir, A. M. ; Koeppl, H. (2018):
Reinforcement Learning in a Continuum of Agents.
In: Swarm Intelligence, 12 (1), pp. 23-51. DOI: 10.1007/s11721-017-0142-9,
[Article]

Bronstein, L. ; Koeppl, H. (2018):
A variational approach to moment-closure approximations for the kinetics of biomolecular reaction networks.
In: The Journal of Chemical Physics, 148 (1), American Institute of Physics (AIP), ISSN 00219606,
DOI: 10.1063/1.5003892,
[Article]

Šošić, A. ; Rueckert, E. ; Peters, J. ; Zoubir, A. M. ; Koeppl, H. (2018):
Inverse Reinforcement Learning via Nonparametric Spatio-Temporal Subgoal Modeling.
In: Journal of Machine Learning Research, 19 (69), pp. 1-45. [Article]

Šošić, A. ; Zoubir, A. M. ; Koeppl, H. (2018):
Inverse Reinforcement Learning via Nonparametric Subgoal Modeling.
In: AAAI Spring Symposium on Data-Efficient Reinforcement Learning, [Conference or Workshop Item]

Yang, S. ; Koeppl, H. (2018):
A Poisson Gamma Probabilistic Model for Latent Node-group Memberships in Dynamic Networks.
AAAI 2018, Association for the Advancement of Artificial Intelligence, New Orleans, 2018, [Conference or Workshop Item]

KhudaBukhsh, W. R. ; Rizk, A. ; Froemmgen, A. ; Koeppl, H. (2017):
Optimizing Stochastic Scheduling in Fork-Join Queueing Models: Bounds and Applications.
In: Technical Program of IEEE INFOCOM 2017, IEEE, [Article]

KhudaBukhsh, W. R. ; Rizk, A. ; Froemmgen, A. ; Koeppl, H. (2017):
Optimizing Stochastic Scheduling in Fork-Join Queueing Models: Bounds and Applications.
In: Technical Program of IEEE INFOCOM 2017, IEEE, [Article]

Ruess, J. ; Koeppl, H. ; Zechner, C. (2017):
Sensitivity estimation for stochastic models of biochemical reaction networks in the presence of extrinsic variability.
In: The Journal of Chemical Physics, 146 (124122), AIP, [Article]

KhudaBukhsh, W. R. ; Woroszylo, C. ; Rempala, G. A. ; Koeppl, H. (2017):
Functional Central Limit Theorem for Susceptible-Infected Process On Configuration Model Graphs.
In: Annals of Applied Probability (under review), 27, [Article]

Šošić, A. ; KhudaBukhsh, W. R. ; Zoubir, A. M. ; Koeppl, H. (2017):
Inverse Reinforcement Learning in Swarm Systems.
In: AAMAS Workshop on Transfer in Reinforcement Learning, [Conference or Workshop Item]

Šošić, A. ; KhudaBukhsh, W. R. ; Zoubir, A. M. ; Koeppl, H. (2017):
Inverse Reinforcement Learning in Swarm Systems (Best Paper Award Finalist).
In: International Conference on Autonomous Agents and Multiagent Systems, [Conference or Workshop Item]

Bronstein, L. ; Diemer, J. ; Koeppl, H. ; Schneider, C. ; Suess, Beatrix (2017):
ROC'n'Ribo: Characterizing a riboswitching expression system by modeling single-cell data.
In: ACS Synthetic Biology, (7), pp. 1211-1224. ACS, ISSN 2161-5063,
[Article]

Bronstein, L. ; Koeppl, H. (2016):
Scalable inference using PMCMC and parallel tempering for high-throughput measurements of biomolecular reaction networks.
55th IEEE Conference on Decision and Control, Las Vegas, December 2016, [Conference or Workshop Item]

Sulaimanov, N. ; Koeppl, H. (2016):
Graph reconstruction using covariance based methods.
In: EURASIP Journal on Bioinformatics and Systems Biology, Springer, [Article]

Bronstein, L. ; Koeppl, H. (2016):
A Diagram Technique for cumulant equations in biomolecular reaction networks with mass-action kinetics.
55th IEEE Conference on Decision and Control, Las Vegas, USA, December 2016, [Conference or Workshop Item]

Ganguly, A. ; Altintan, D. ; Koeppl, H. (2016):
Efficient Simulation of Multiscale Reaction.
American Control Conference, Boston, Juli 2016, [Conference or Workshop Item]

Hill, S. M. ; Heiser, L. M. ; Cokalaer, T. ; Unger, M. ; Nesser, N. K. ; Carlin, D. E. ; Zhang, Y. ; Sokolov, A. ; Paull, E. O. ; Wong, C. K. ; Graim, K. ; Bivol, A. ; Wang, H. ; Zhu, F. ; Afsari, B. ; Danilova, L. V. ; Favorov, A. V. ; Lee, W. S. ; Taylor, D. ; Hu, C. W. ; Long, B. L. ; Noren, D. P. ; Bisberg, A. J. ; Mills, G. B. ; Gray, J. W. ; Kellen, M. ; Norman, T. ; Friend, S. ; Qutub, A. A. ; Fertig, E. J. ; Guan, Y. ; Song, M. ; Stuart, J. M. ; Spellman, P. T. ; Koeppl, H. ; Stolovitzky, G. ; Saez-Rodriguez, J. ; Mukherjee, S. (2016):
Interferring causal molecular networks: empirical assessment through a community-based effort.
In: Nature methods, 13 (4), pp. 310-318. Nature Publishing Group, e-ISSN 1548-7105,
[Article]

Studer, L. ; Paulevé, L. ; Zechner, C. ; Reumann, M. ; Rodriguez Martinez, M. ; Koeppl, H. (2016):
Marginalized Continuous Time Bayesian Networks for Network Reconstruction from Incomplete Observations.
Phoenix, USA, AAAI, Association for the Advancement of Artificial Intelligence, Phoenix, USA, 12.-17.02.2016, [Conference or Workshop Item]

KhudaBukhsh, W. R. ; Rueckert, J. ; Wulfheide, J. ; Hausheer, D. ; Koeppl, H. (2016):
Analysing and Leveraging Client Heterogeneity in Swarming-based Live Streaming.
In: IFIP International Conference on Networking (NETWORKING), pp. 386-394,
IFIP International Conference on Networking, Wien, Austria, Mai 2016, [Conference or Workshop Item]

KhudaBukhsh, W. R. ; Rueckert, J. ; Wulfheide, J. ; Hausheer, D. ; Koeppl, H. (2016):
Analysing and Leveraging Client Heterogeneity in Swarming-based Live Streaming.
pp. 386-394, IFIP International Conference on Networking (NETWORKING), [Conference or Workshop Item]

Richerzhagen, B. ; Wulfheide, J. ; Koeppl, H. ; Mauthe, A. U. ; Nahrstedt, K. ; Steinmetz, R. (2016):
Enabling Crowdsourced Live Event Coverage with Adaptive Collaborative Upload Strategies.
In: 2016 IEEE 17th International Symposium on "A World of Wireless, Mobile and Multimedia Networks" (WoWMoM),
Coimbra, Portugal, [Conference or Workshop Item]

Šošić, A. ; Zoubir, A. M. ; Koeppl, H. (2016):
Policy Recognition via Expectation Maximization.
IEEE International Conference on Acoustics, Speech and Signal Processing, DOI: 10.1109/ICASSP.2016.7472589,
[Conference or Workshop Item]

Huang, L. ; Hansen, A. S. ; Pauleve, L. ; Unger, M. ; Zechner, C. ; Koeppl, H. (2016):
Reconstructing dynamic molecular states from single-cell time series.
In: Journal of The Royal Society Interface, 13 (122), Royal Society Publishing, ISSN 1742-5689,
[Article]

Sutter, T. ; Ganguly, A. ; Koeppl, H. (2016):
A variational approach to path estimation and parameter inference of hidden diffusion processes.
In: Journal of Machine Learning Research, 17 (190), pp. 1-37. [Article]

Hegemann, B. ; Unger, M. ; Lee, S. S. ; Stoffel-Studer, I. ; Heuvel, J. van den ; Pelet, S. ; Koeppl, H. ; Peter, M. (2015):
A Cellular System for Spatial Signal Decoding in Chemical Gradients.
In: Developmental Cell, 35 (4), pp. 458-470. Elsevier, [Article]

Huang, L. ; Hjalmarsson, H. ; Koeppl, H. (2015):
Almost sure stability and stabilization of discrete-time stochastic systems.
In: Systems & Control Letters, 82, pp. 26-32. [Article]

Altintan, D. ; Ganguly, A. ; Koeppl, H. (2015):
Error bound and simulation algorithm for piecewise deterministic approximations of stochastic reaction systems.
In: American Control Conference (ACC), 2015,
American Control Conference (ACC), 2015, Chicago, 1-3 July 2015, [Conference or Workshop Item]

Bronstein, L. ; Zechner, C. ; Koeppl, H. (2015):
Bayesian inference of reaction kinetics from single-cell recordings across a heterogeneous cell population.
In: ScienceDirect - Methods, 85, pp. 22-35. Elsevier, [Article]

KhudaBukhsh, W. R. ; Rueckert, J. ; Wulfheide, J. ; Hausheer, D. ; Koeppl, H.
KhudaBukhsh W. R. (Corporate Creator) (2015):
A Comprehensive Analysis of Swarming-based Live Streaming to Leverage Client Heterogenieity.
In: Technical Report, Darmstadt, Technische Universität Darmstadt, [Report]

Altintan, D. ; Ganguly, A. ; Koeppl, H. (2015):
Jump-Diffusion Approximation of Stochastic Reaction Dynamics: Error bounds and Algorithms.
In: SIAM Multiscale Modeling and Simulation, 13 (4), SIAM (Society for Industrial and Applied Mathematics), ISSN 1540-3459,
[Article]

Geiger, B. C. ; Petrov, T. ; Kubin, G. ; Koeppl, H. (2015):
Optimal Kullback-Leibler Aggregation via Information Bottleneck.
In: IEEE Transactions on Automatic Control, 60 (4), pp. 1010-1022. IEEE, ISSN 0018-9286,
[Article]

Koeppl, H. ; Zechner, C. (2014):
Uncoupled analysis of stochastic reaction networks in fluctuating environments.
In: PLOS Computational Biology, 10 (12), Cornell University, ISSN 1476-928X,
[Article]

Koeppl, H. ; Hafner, M. ; Lu, J. (2014):
From Specification to Parameters: A Linearization Approach.
Part II, In: A Systems Theoretic Approach to Systems and Synthetic Biology II: Analysis and Design of Cellular Systems, pp. 245-256, Netherlands, Springer, ISBN 978-94-017-9046-8,
[Book Section]

Zechner, C. ; Unger, M. ; Pelet, S. ; Peter, M. ; Koeppl, H. (2014):
Scalable inference of heterogeneous reaction kinetics from pooled single-cell recordings.
In: Nature methods, 11 (2), pp. 197-202. [Article]

Zechner, C. ; Wadehn, F. ; Koeppl, H. (2014):
Sparse learning of Markovian population models in random environments.
pp. 1723-1728, Cornell, IFAC 2014, The 19th World Congress of the International Federation of Automatic Control, Promoting automatic control for the benefit of humankind, Cape Town, South Africa, 24-29 August 2014, [Conference or Workshop Item]

Ganguly, A. ; Petrov, T. ; Koeppl, H. (2013):
Markov chain aggregation and its applications to combinatorial reaction networks.
In: Journal of mathematical biology, 69 (3), pp. 767-797. [Article]

Tarca, A. L. ; Lauria, M. ; Unger, M. ; Bilal, E. ; Boue, S. ; Kumar Dey, K. ; Hoeng, J. ; Koeppl, H. ; Martin, F. ; Meyer, P. ; Nandy, P. ; Norel, R. ; Peitsch, M. ; Rice, J. ; Romero, R. ; Stolovitzky, G. ; Talikka, M. ; Xiang, Y. ; Zechner, C. (2013):
Strengths and limitations of microarray-based phenotype prediction: lessons learned from the IMPROVER Diagnostic Signature Challenge.
In: Bioinformatics (Oxford, England), 29 (22), pp. 2892-2899. [Article]

Heras Ciechomski, P. de ; Klann, M. ; Mange, R. ; Koeppl, H. (2013):
From biochemical reaction networks to 3D dynamics in the cell: The ZigCell3D modeling, simulation and visualisation framework.
pp. 41-48, IEEE, 2013 IEEE Symposium on Biological Data Visualization (BioVis), Atlanta, USA, 13.-14.10.2013, ISBN 978-1-4799-1658-0,
DOI: 10.1109/BioVis.2013.6664345,
[Conference or Workshop Item]

Klann, M. ; Koeppl, H. (2013):
Reaction schemes, escape times and geminate recombinations in particle-based spatial simulations of biochemical reactions.
In: Physical biology, 10 (4), pp. 046005. [Article]

Lu, J. ; August, E. ; Koeppl, H. (2013):
Inverse problems from biomedicine : Inference of putative disease mechanisms and robust therapeutic strategies.
In: Journal of mathematical biology, 67 (1), pp. 143-168. Springer Verlag, ISSN 0303-6812,
[Article]

Paulevé, L. ; Craciun, G. ; Koeppl, H. (2013):
Dynamical properties of Discrete Reaction Networks.
In: Journal of mathematical biology, 69, pp. 55-72. [Article]

Nandy, P. ; Unger, M. ; Zechner, C. ; Dey, K. ; Koeppl, H. (2013):
Learning diagnostic signatures from microarray data using Ll-regularized logistic regression.
In: Systems Biomedicine, 1 (4), Taylor & Francis, [Article]

Koeppl, H. ; Petrov, T. (2013):
Approximate model reductions for combinatorial reaction systems; European Control Conferenc (ECC 2013).
pp. 4172-4177, European Control Conferenc (ECC 2013), Zuerich, 17-19 July 2013, [Conference or Workshop Item]

Klann, M. ; Paulevé, L. ; Petrov, T. ; Koeppl, H. (2013):
Coarse-Grained Brownian Dynamics Simulation of Rule-Based Models.
8130, pp. 64-77, Springer Berlin Heidelberg, 11th International Conference on Computational Methods in Systems Biology (CMSB 2013), [Conference or Workshop Item]

Koeppl, H. ; Hafner, M. ; Lu, J. (2013):
Mapping behavioral specifications to model parameters in synthetic biology.
In: BMC Bioinformatics, 14, pp. S9. [Article]

Zechner, C. ; Deb, S. ; Koeppl, H. (2013):
Marginal dynamics of stochastic biochemical networks in random environments.
pp. 4269-4274, IEEE, 2013 European Control Conference (ECC), Zürich, 2013, [Conference or Workshop Item]

Feret, J. ; Koeppl, H. ; Petrov, T. (2013):
Stochastic fragments: A framework for the exact reduction of the stochastic semantics of rule-based models.
In: International Journal of Software and Informatics, 7 (4), pp. 527-604. [Article]

Paulevé, L. ; Andrieux, G. ; Koeppl, H. (2013):
Under-approximating cut sets for reachability in large scale automata Networks.
8044, pp. 69-84, Springer, 25th International Conference on Computer Aided Verification (CAV 2013), [Conference or Workshop Item]

August, E. ; Koeppl, H. (2012):
Computing enclosures for uncertain biochemical systems.
In: IET Systems Biology, 6 (6), pp. 232-240. [Article]

August, E. ; Craciun, G. ; Koeppl, H. (2012):
Finding invariant sets for biological systems using monomial domination.
pp. 3001-3006, Maui, HI, USA, IEEE, 51st IEEE Conference on Decision and Control (CDC), 2012, 2012, [Conference or Workshop Item]

Zechner, C. ; Nandy, P. ; Unger, M. ; Koeppl, H. (2012):
Optimal variational perturbations for the inference of stochastic reaction dynamics.
pp. 5336-5341, IEEE, 2012 IEEE 51st IEEE Conference on Decision and Control (CDC), [Conference or Workshop Item]

Petrov, T. ; Feret, J. ; Koeppl, H. (2012):
Reconstructing species-based dynamics from reduced stochastic rule-based models.
p. 15, ACM, 2012 Winter Simulation Conference (WSC'12), Berlin, Germany, 09.-12.12., [Conference or Workshop Item]

Klann, M. ; Ganguly, A. ; Koeppl, H. (2012):
Hybrid spatial Gillespie and particle tracking simulation.
In: Bioinformatics (Oxford, England), 28 (18), pp. i549. [Article]

Koeppl, H. ; Zechner, C. ; Ganguly, A. ; Pelet, S. ; Peter, M. (2012):
Accounting for extrinsic variability in the estimation of stochastic rate constants.
In: International Journal of Robust and Nonlinear Control, 22 (10), pp. 1103-1119. Wiley-Blackwell, [Article]

Nandy, P. ; Unger, M. ; Zechner, C. ; Koeppl, H. (2012):
Optimal Perturbations for the Identification of Stochastic Reaction Dynamics.
pp. 686-691, Elsevier, 16th IFAC Symposium on System Identification, [Conference or Workshop Item]

Petrov, T. ; Ganguly, A. ; Koeppl, H. (2012):
Model Decomposition and Stochastic Fragments.
In: Electronic Notes in Theoretical Computer Science, 284, pp. 105-124. [Article]

Pantea, C. ; Koeppl, H. ; Craciun, G. (2012):
Global injectivity and multiple equilibria in uni- and bi-molecular reaction networks.
In: Discrete and Continuous Dynamical Systems - Series B, 17 (6), pp. 2153-2170. American Institute of Mathematical Sciences, [Article]

Zechner, C. ; Ruess, J. ; Krenn, P. ; Pelet, S. ; Peter, M. ; Lygeros, J. ; Koeppl, H. (2012):
Moment-based inference predicts bimodality in transient gene expression.
In: Proceedings of the National Academy of Sciences of the United States of America, 109 (21), pp. 8340-8345. [Article]

Feret, J. ; Henzinger, T. ; Koeppl, H. ; Petrov, T. (2012):
Lumpability Abstractions of Rule-based Systems.
In: Journal of Theoretical Comuter Science, 431, pp. 137-164. [Article]

Hafner, M. ; Koeppl, H. ; Gonze, D. (2012):
Effect of network architecture on synchronization and entrainment properties of the circadian oscillations in the suprachiasmatic nucleus.
In: PLoS computational biology, 8 (3), pp. e1002419. [Article]

Hiroi, N. ; Klann, M. ; Iba, K. ; Heras Ciechomski, P. de ; Yamashita, S. ; Tabira, A. ; Okuhara, T. ; Kubojima, T. ; Okada, Y. ; Oka, K. ; Mange, R. ; Unger, M. ; Funahashi, A. ; Koeppl, H. (2012):
From microscopy data to in silico environments for in vivo-oriented simulations.
In: EURASIP Journal on Bioinformatics and Systems Biology, 2012 (1), p. 7. [Article]

Klann, M. ; Koeppl, H. ; Reuss, M. (2012):
Spatial modeling of vesicle transport and the cytoskeleton: the challenge of hitting the right road.
In: PloS one, 7 (1), pp. e29645. [Article]

Klann, M. ; Koeppl, H. (2012):
Spatial simulations in systems biology: from molecules to cells.
In: International journal of molecular sciences, 13 (6), pp. 7798-7827. [Article]

Koeppl, H. ; Petrov, T. (2012):
Reductions of stochastic rule-based models: HOG pathway in yeast.
ICSB : The 13th International Conference on Systems Biology, [Conference or Workshop Item]

Klann, M. ; Koeppl, H. (2012):
Spatial stochastic simulation of transcription factor binding reveals mechaniscms to control gene activation.
61, pp. 51-54, Tampere University of Technology, Tampere International Center for Signal Processing, 9th International Workshop on Computational Systems Biology (WCSB 2012), [Conference or Workshop Item]

August, E. ; Lu, J. ; Koeppl, H. (2012):
Trajectory enclosures for systems with uncertainties in initial conditions and parameter values.
pp. 1488-1493, Fairmont Queen Elizabeth, Montreal, Canada, 2012 American Control Conference, Fairmont Queen Elizabeth, Montreal, Canada, 2012, [Conference or Workshop Item]

Zechner, C. ; Pelet, S. ; Peter, M. ; Koeppl, H. (2011):
Recursive Bayesian estimation of stochastic rate constants from heterogeneous cell populations.
In: IEEE Conference on Decision and Control and European Control Conference, pp. 5837-5843. IEEE, [Article]

Koeppl, H. ; Hafner, M. ; Ganguly, A. ; Mehrotra, A. (2011):
Deterministic characterization of phase noise in biomolecular oscillators.
In: Physical biology, 8 (5), p. 55008. [Article]

Meyer, P. ; Alexopoulos, L. G. ; Bonk, T. ; Califano, A. ; Cho, C. R. ; Fuente, A. de la ; Graaf, D. de ; Hartemink, A. J. ; Hoeng, J. ; Ivanov, N. V. ; Koeppl, H. ; Linding, R. ; Marbach, D. ; Norel, R. ; Peitsch, M. C. ; Rice, J. J. ; Royyuru, A. ; Schacherer, F. ; Sprengel, J. ; Stolle, K. ; Vitkup, D. ; Stolovitzky, G. (2011):
Verification of systems biology research in the age of collaborative competition.
In: Nature biotechnology, 29 (9), pp. 811-815. [Article]

Koeppl, H. ; Petrov, T. (2011):
Stochastic Semantics of Signaling as a Composition of Agent-view Automata.
In: Electronic Notes in Theoretical Computer Science, 272, pp. 3-17. [Article]

Lu, J. ; Grass, P. ; Koeppl, H. (2011):
Computational identification of optimal multi target drug intervention strategies for combination theory.
p. 132, Zurich, Eighth International Workshop on Computational Systems Biology, WCSB 2011, June 6-8, 2011, Zurich, Switzerland, [Conference or Workshop Item]

August, E. ; Wang, Y. ; Doyle, F. J. ; Lu, J. ; Koeppl, H. (2011):
Computationally implementable sufficient conditions for the synchronisation of coupled dynamical systems with time delays in the coupling.
pp. 839-844, San Francisco, CA, USA, IEEE, Proceedings of the 2011 American Control Conference, [Conference or Workshop Item]

Danos, V. ; Koeppl, H. ; Wilson-Kanamori, J. (2011):
Cooperative assembly systems.
pp. 1-21, Springer, 17th International Conference on DNA-Based Computers (DNA 2011), Pasadena, USA, 19.-23.09., ISBN 978-3-642-23637-2,
DOI: 10.1007/978-3-642-23638-9_1,
[Conference or Workshop Item]

Koeppl, H. ; Andreozzi, S. ; Steuer, R. (2011):
Guaranteed and Randomized Methods for Stability Analysis of Uncertain Metabolic Networks.
In: Lecture notes in control and information sciences, 407, pp. 297-309. Springer, [Article]

Klann, M. ; Ganguly, A. ; Koeppl, H. (2011):
Improved Reaction Scheme for Spatial Stochastic Simulations with Single Molecule Detail.
57, pp. 93-96, Tampere, Tampere University of Technology, Eighth International Workshop on Computational Systems Biology (WCSB 2011), [Conference or Workshop Item]

Falk, M. ; Ott, M. ; Ertl, T. ; Klann, M. ; Koeppl, H. (2011):
Parallelized Agent-based Simulation on CPU and Graphics Hardware for Spatial and Stochastic Models in Biology Categories and Subject Descriptors.
In: CMSB '11 Proceedings of the 9th International Conference on Computational Methods in Systems Biology, pp. 73-82,
New York, New York, USA, ACM Press, [Conference or Workshop Item]

Unger, M. ; Lee, S.-S. ; Peter, M. ; Koeppl, H. (2011):
Pulse Width Modulation of Liquid Flows.
pp. 1567-1569, San Diego, CA, Chemical and Biological Microsystems Society, 15th International Conference on Miniaturized Systems for Chemistry and Life Sciences, [Conference or Workshop Item]

Hafner, M. ; Lu, J. ; Petrov, T. ; Koeppl, H. (2011):
Rational design of robust biomolecular circuits: From specification to parameters.
In: Analysis and Design of Biomolecular Circuits, pp. 253-281, New York, NY, Springer, [Book Section]

Hafner, M. ; Koeppl, H. (2011):
Stochastic Simulations in Systems Biology.
1, In: Handbook of Research on Computational Science and Engineering: Theory and Practice, pp. 267-286, IGI Global, [Book Section]

Camporesi, F. ; Feret, J. ; Koeppl, H. ; Petrov, T. (2010):
Combining Model Reductions.
In: Electronic Notes in Theoretical Computer Science, 265, pp. 73-96. [Article]

Petrov, T. ; Koeppl, H. (2010):
Maximal reduction of deterministic semantics of rule-based models - Google-Suche.
pp. 83-87, Proceedings of the International Workshop on computational Systems Biology (WCSB) in 2010, [Conference or Workshop Item]

Koeppl, H. ; Setti, G. ; Pelet, S. ; Mangia, M. ; Petrov, T. ; Peter, M. (2010):
Probability metrics to calibrate stochastic chemical kinetics.
In: Circuits and Systems (ISCAS), Proceedings of 2010 IEEE International Symposium on, [Article]

Hafner, M. ; Koeppl, H. ; Hasler, M. ; Wagner, A. (2009):
'Glocal' robustness analysis and model discrimination for circadian oscillators.
In: PLoS Computational Biology, 5 (10), pp. e1000534. [Article]

Koeppl, H. ; Setti, G. (2009):
Analysis and design of biological circuits and systems.
pp. 297-300, Taipeh, Taiwan, IEEE, 2009 IEEE International Symposium on Circuits and Systems, [Conference or Workshop Item]

Rodrigues, A. ; Koeppl, H. ; Ohtsuki, H. ; Satake, A. (2009):
A Game Theoretical Model of deforestation in human-environment relationships.
In: Journal of Theoretical Biology, 258 (1), pp. 127-134. [Article]

Koeppl, H. (2009):
A Local Nonlinear Model for the Approximation and Identification of a Class of Systems.
In: IEEE Transactions on Circuits and Systems II: Express Briefs, 56 (4), pp. 315-319. [Article]

Parisi, F. ; Koeppl, H. ; Naef, F. (2009):
Network inference by combining biologically motivated regulatory constraints with penalized regression.
In: Annals of the New York Academy of Sciences, 1158, pp. 114-124. [Article]

Hafner, M. ; Koeppl, H. ; Wagner, A. (2009):
Robustness and evolution in oscillatory systems with feedback loops.
p. 4, Denver, USA, IEEE, Proc. of the Third IEEE International Conference on Foundations of Systems Biology in Engineering (FOSBE), [Conference or Workshop Item]

Koeppl, H. ; Haeusler, S. (2009):
Motifs, algebraic connectivity and computational performance of two data- based cortical circuit templates.
In: Proceedings of the sixth International Workshop on Computational Systems Biology, pp. 83-86. [Article]

Hafner, M. ; Danos, V. ; Koeppl, H. (2009):
Rule-based modeling for protein-protein interaction networks - the Cyanobacterial circadian clock as a case studyproceedings.
pp. 87-90, Aarhus, Denmark, Proceedings of the International Workshop on Computational Systems Biology (WCSB), [Conference or Workshop Item]

Koeppl, H. ; Hafner, M. ; Steuer, R. (2009):
Semi-quantitative stability analysis constrains saturation levels in metabolic networks.
pp. 91-94, Aarhus, Denmark, Proceedings of the Intenational Workshop on Computational Systems Biology (WCSB), [Conference or Workshop Item]

Koeppl, H. ; Schumacher, L. ; Danos, V. (2009):
A Statistical analysis of receptor.
pp. 95-98, Aarhus, Denmark, Proceedings of the International Workshop on Computtional Systmes Biology (WCSB), [Conference or Workshop Item]

Krall, C. ; Witrisal, K. ; Leus, G. ; Koeppl, H. (2008):
Minimum Mean-Square Error Equalization for Second-Order Volterra Systems.
In: IEEE Transactions on Signal Processing, 56 (10), pp. 4729-4737. IEEE, [Article]

Murmann, B. ; Vogel, C. ; Koeppl, H. (2008):
Digitally enhanced analog circuits: System aspects.
pp. 560-563, IEEE, 2008 IEEE International Symposium on Circuits and Systems, [Conference or Workshop Item]

Singerl, P. ; Koeppl, H. (2007):
A Low-rate identification method for digital predistorters based on Volterra kernel interpolation.
In: Analog Integrated Circuits and Signal Processing, 56 (1-2), pp. 107-115. Springer, [Article]

Koeppl, H. (2007):
The Composition Rule for Multivariate Volterra Operators and its Application to Circuit Analysis.
pp. 441-444, IEEE, 2007 IEEE International Symposium on Circuits and Systems, [Conference or Workshop Item]

Koeppl, H. ; Chua, L. O. (2007):
An Adaptive Cellular Nonlinear Network and its Application.
In: Proceedings of the International Symposium on Nonlinear Theory and its Applications (NOLTA), pages 15–18, Sept. 16-19, 2007, Vancouver, Canada., [Article]

Huang, C.-H. ; Koeppl, H. (2007):
A Bio-inspired Computer Fovea Model based on hexagonal-type cellular neural networks.
In: IEEE Transactions on circuits and systems-I : regular papers, 54 (1), IEEE, [Article]

Wolkerstorfer, M. ; Koeppl, H. (2007):
On the Projection Dynamic for Selfish Routing.
Dresden, Germany, European Complex Systems Conference, [Conference or Workshop Item]

Koeppl, H. ; Singerl, P. (2006):
An Efficient Scheme for Nonlinear Modeling and Predistortion in Mixed-Signal Systems.
In: IEEE Transactions on Circuits and Systems II: Express Briefs, 53 (12), pp. 1368-1372. [Article]

Koeppl, H. (2006):
An Adaptive Cellular Network for Subspace Extraction.
pp. 1037-1041, Pacific Grove, CA, USA, IEEE, 2006 Fortieth Asilomar Conference on Signals, Systems and Computers, [Conference or Workshop Item]

Koeppl, H. (2006):
Information Rate Maximization over a Resistive Grid.
pp. 5196-5203, Vancouver, BC, IEEE, The 2006 IEEE International Joint Conference on Neural Network Proceedings, [Conference or Workshop Item]

Singerl, P. ; Koeppl, H. (2005):
A Low-rate identification method for digital predistorters based on Volterra kernel interpolation.
In: Circuits and Systems, 2005. 48th Midwest Symposium, 2, pp. 1533-1536. IEEE, [Article]

Schwingshackl, D. ; Koeppl, H. ; Kubin, G. (2005):
Exact discrete-time representation of continuous-time Volterra filters.
In: NSIP 2005. Abstracts. IEEE-Eurasip Nonlinear Signal and Image Processing, 2005., p. 11. IEEE, [Article]

Krall, C. ; Witrisal, K. ; Koeppl, H. ; Leus, G. ; Pausini, M. (2005):
Nonlinear equalization for frame-differential IR-UWB receivers.
In: 2005 IEEE International Conference on Ultra-Wideband, pp. 576-581. IEEE, [Article]

Singerl, P. ; Koeppl, H. (2005):
Volterra kernel interpolation for system modeling and predistortion purposes.
1, pp. 251-254, IEEE, International Symposium on Signals, Circuits and Systems, 2005. ISSCS 2005., [Conference or Workshop Item]

Shutin, D. ; Koeppl, H. (2004):
Application of the Evidence Procedure to Linear Problems in Signal Processing.
735, pp. 161-168, AIP, AIP Conference Proceedings, [Conference or Workshop Item]

Koeppl, H. ; Josan, A. S. ; Paoli, G. ; Kubin, G. (2004):
The Cramer-Rao Bound and DMT Signal Optimisation for the Identification of a Wiener-Type Model.
In: EURASIP Journal on Applied Signal Processing, 12, pp. 1817-1830. [Article]

Koeppl, H. ; Schwingshackl, D. (2004):
Comparison of discrete-time approximations for continuous-time nonlinear systems.
In: 2004 IEEE International Conference on Acoustics, Speech, and Signal Processing, 2, pp. ii-881. IEEE, [Article]

Koeppl, H. (2004):
Nonlinear System Identification for Mixed Signal Processing | Signal Processing and Speech Communication Laboratory.
Graz Universitay of Technology, Graz, Austria,
[Ph.D. Thesis]

Koeppl, H. ; Kubin, G. ; Paoli, G. (2003):
Bayesian methods for sparse RLS adaptive filters.
2, pp. 1273-1277, Pacific Grove, CA, USA, IEEE, The Thrity-Seventh Asilomar Conference on Signals, Systems & Computers, 2003, [Conference or Workshop Item]

Vogel, C. ; Koeppl, H. (2003):
Behavioral Modeling of Time-Interleaved ADCs using MATLAB.
pp. 45-48, Austrochip 2003, Linz, Austria, 03.-12.10.2003, [Conference or Workshop Item]

Koeppl, H. ; Paoli, G. ; Kubin, G. (2003):
The Cramer-Rao bound for a factorizable Volterra system.
Grado, Italy, IEEE, IEEE Workshop on Nonlinear Signal and Image Processing, [Conference or Workshop Item]

Koeppl, H. ; Paoli, G. (2002):
Non-Linear System Identification of a Broadband Subscriber Line Interface Circuitry Using the Volterra Approach.
In: Mathematics in Signal Processing V, V (Chapter 13), Oxford University Press, [Article]

Koeppl, H. ; Paoli, G. (2002):
Non-linear modeling of a broadband SLIC for ADSL-Lite-over-POTS using harmonic analysis.
2, pp. II-133, Scottsdale, Arizona, USA, IEEE, 2002 IEEE International Symposium on Circuits and Systems. Proceedings (Cat. No.02CH37353), [Conference or Workshop Item]

Koeppl, H. (2001):
Identification of a non-linear analog circuitry for an ADSL application.
Karl-Franzens-Universität, Graz, Austria, [Master Thesis]

Paoli, G. ; Koeppl, H. (2001):
Non-linear identification and modeling of large scale analog integrated circuitties for DMT based applications.
pp. 84-87, Bratislava, Slovakia, Proc. of the Electronic Circuits and Systems Conference, [Conference or Workshop Item]

Koeppl, H. ; Paoli, G.
The Institute of Mathematics and its Applications (IMA) (Corporate Creator) (2000):
Non-Linear System Identification of a Broadband Subscriber Line Interface Circuit for ADSL-Lite Using the Volterra Approach.
pp. 359-362, 5th IMA International Conference on Mathematics in Signal Processing, Warwick, United Kingdom, [Conference or Workshop Item]