| Safe active learning for time-series modeling with gaussian processes C Zimmer, M Meister, D Nguyen-Tuong Advances in neural information processing systems 31, 2018 | 52 | 2018 |
| Parameter estimation for stochastic models of biochemical reactions C Zimmer | 26 | 2012 |
| Use of daily Internet search query data improves real-time projections of influenza epidemics C Zimmer, SI Leuba, R Yaesoubi, T Cohen Journal of The Royal Society Interface 15 (147), 20180220, 2018 | 19 | 2018 |
| Deterministic inference for stochastic systems using multiple shooting and a linear noise approximation for the transition probabilities C Zimmer, S Sahle IET Systems Biology 9 (5), 181-192, 2015 | 17 | 2015 |
| A likelihood approach for real-time calibration of stochastic compartmental epidemic models C Zimmer, R Yaesoubi, T Cohen PLoS computational biology 13 (1), e1005257, 2017 | 15 | 2017 |
| Influenza forecasting framework based on Gaussian processes C Zimmer, R Yaesoubi International Conference on Machine Learning, 11671-11679, 2020 | 14 | 2020 |
| A new efficient approach to fit stochastic models on the basis of high-throughput experimental data using a model of IRF7 gene expression as case study LU Aguilera, C Zimmer, U Kummer BMC systems biology 11 (1), 1-14, 2017 | 14 | 2017 |
| Tracking and predicting US influenza activity with a real-time surveillance network SI Leuba, R Yaesoubi, M Antillon, T Cohen, C Zimmer PLoS computational biology 16 (11), e1008180, 2020 | 13 | 2020 |
| Accurate quantification of uncertainty in epidemic parameter estimates and predictions using stochastic compartmental models C Zimmer, SI Leuba, T Cohen, R Yaesoubi Statistical methods in medical research 28 (12), 3591-3608, 2019 | 13 | 2019 |
| Experimental design for stochastic models of nonlinear signaling pathways using an interval-wise linear noise approximation and state estimation C Zimmer PloS one 11 (9), e0159902, 2016 | 12 | 2016 |
| Reconstructing the hidden states in time course data of stochastic models C Zimmer Mathematical BioSciences 269, 117-129, 2015 | 12 | 2015 |
| Exploiting intrinsic fluctuations to identify model parameters C Zimmer, S Sahle, J Pahle IET systems biology 9 (2), 64-73, 2015 | 12 | 2015 |
| Piecewise parameter estimation for stochastic models in COPASI FT Bergmann, S Sahle, C Zimmer Bioinformatics 32 (10), 1586-1588, 2016 | 10 | 2016 |
| Comparison of approaches for parameter estimation on stochastic models: Generic least squares versus specialized approaches C Zimmer, S Sahle Computational biology and chemistry 61, 75-85, 2016 | 8 | 2016 |
| Estimation of kinetic parameters of transcription from temporal single-RNA measurements C Zimmer, A Häkkinen, AS Ribeiro Mathematical Biosciences 271, 146-153, 2016 | 8 | 2016 |
| Safe active learning for multi-output gaussian processes CY Li, B Rakitsch, C Zimmer International Conference on Artificial Intelligence and Statistics, 4512-4551, 2022 | 7 | 2022 |
| Cost-effectiveness of alternative uses of polyvalent meningococcal vaccines in Niger: an agent-based transmission modeling study SMN Arifin, C Zimmer, C Trotter, A Colombini, F Sidikou, FM LaForce, ... Medical Decision Making 39 (5), 553-567, 2019 | 6 | 2019 |
| Structural kernel search via bayesian optimization and symbolical optimal transport M Bitzer, M Meister, C Zimmer Advances in Neural Information Processing Systems 35, 39047-39058, 2022 | 5 | 2022 |
| Active Learning in Gaussian Process State Space Model HSA Yu, D Yao, C Zimmer, M Toussaint, D Nguyen-Tuong Machine Learning and Knowledge Discovery in Databases. Research Track …, 2021 | 4 | 2021 |
| Hierarchical-Hyperplane Kernels for Actively Learning Gaussian Process Models of Nonstationary Systems M Bitzer, M Meister, C Zimmer International Conference on Artificial Intelligence and Statistics, 7897-7912, 2023 | 3 | 2023 |
