| Fovea-like photoreceptor specializations underlie single UV cone driven prey-capture behavior in zebrafish T Yoshimatsu, C Schröder, NE Nevala, P Berens, T Baden Neuron 107 (2), 320-337. e6, 2020 | 140 | 2020 |
| Ancestral circuits for vertebrate color vision emerge at the first retinal synapse T Yoshimatsu, P Bartel, C Schröder, FK Janiak, F St-Pierre, P Berens, ... Science Advances 7 (42), eabj6815, 2021 | 46* | 2021 |
| Bayesian inference for biophysical neuron models enables stimulus optimization for retinal neuroprosthetics J Oesterle, C Behrens, C Schröder, T Hermann, T Euler, K Franke, ... Elife 9, e54997, 2020 | 35 | 2020 |
| “How is your thesis going?”–Ph. D. students’ perspectives on mental health and stress in academia J Friedrich, A Bareis, M Bross, Z Bürger, Á Cortés Rodríguez, ... Plos one 18 (7), e0288103, 2023 | 27 | 2023 |
| Approximate bayesian inference for a mechanistic model of vesicle release at a ribbon synapse C Schröder, B James, L Lagnado, P Berens Advances in Neural Information Processing Systems, 2019 | 16 | 2019 |
| Distinct synaptic transfer functions in same-type photoreceptors C Schroeder, J Oesterle, P Berens, T Yoshimatsu, T Baden Elife 10, e67851, 2021 | 14 | 2021 |
| System Identification with Biophysical Constraints: A Circuit Model of the Inner Retina C Schröder, D Klindt, S Strauss, K Franke, M Bethge, T Euler, P Berens Advances in Neural Information Processing Systems, 2020 | 13 | 2020 |
| A practical guide to sample-based statistical distances for evaluating generative models in science S Bischoff, A Darcher, M Deistler, R Gao, F Gerken, M Gloeckler, L Haxel, ... arXiv preprint arXiv:2403.12636, 2024 | 10* | 2024 |
| Differentiable simulation enables large-scale training of detailed biophysical models of neural dynamics M Deistler, KL Kadhim, M Pals, J Beck, Z Huang, M Gloeckler, ... bioRxiv, 2024.08. 21.608979, 2024 | 3 | 2024 |
| Simultaneous identification of models and parameters of scientific simulators C Schröder, JH Macke arXiv preprint arXiv:2305.15174, 2023 | 3 | 2023 |
| Sourcerer: Sample-based maximum entropy source distribution estimation J Vetter, G Moss, C Schröder, R Gao, JH Macke Advances in Neural Information Processing Systems 37, 88772-88806, 2024 | 2 | 2024 |
| Simulation-Based Inference of Surface Accumulation and Basal Melt Rates of an Antarctic Ice Shelf from Isochronal Layers G Moss, V Višnjević, O Eisen, FM Oraschewski, C Schröder, JH Macke, ... arXiv preprint arXiv:2312.02997, 2023 | 1 | 2023 |
| Modelling functional wiring and processing from retinal bipolar to ganglion cells D Klindt, C Schröder, A Vlasits, K Franke, P Berens, T Euler Cosyne Abstract, 2021, 2021 | 1 | 2021 |
| sbi reloaded: a toolkit for simulation-based inference workflows J Boelts, M Deistler, M Gloeckler, Á Tejero-Cantero, JM Lueckmann, ... arXiv preprint arXiv:2411.17337, 2024 | | 2024 |
| Uncertainty mapping and probabilistic tractography using Simulation-Based Inference in diffusion MRI: A comparison with classical Bayes JP Manzano-Patrón, M Deistler, C Schröder, T Kypraios, PJ Gonçalves, ... bioRxiv, 2024.11. 19.624267, 2024 | | 2024 |
| Determining Basal Mass Balance of Ice Shelves Using Simulation-Based Inference G Moss, V Višnjević, C Schröder, J Macke, R Drews EGU General Assembly Conference Abstracts, EGU-6900, 2023 | | 2023 |
| Uncertainty quantification for melt rate parameters in ice shelves using simulation-based inference G Moss, V Višnjević, C Schröder, J Macke, R Drews EGU General Assembly Conference Abstracts, EGU22-896, 2022 | | 2022 |
| From Synapses to Circuits: Different Levels of Functional Modeling of the Retina C Schröder University Tübingen, 2022 | | 2022 |
| UV-cones differentially encode contrast in vivo to support distinct visual functions across visual space T Yoshimatsu, C Schröder, P Berens, T Baden Investigative Ophthalmology & Visual Science 60 (9), 586-586, 2019 | | 2019 |
| Photoreceptor synapses are tuned to environmental statistics in the larval zebrafish C Schröder, P Berens, T Yoshimatsu, T Baden Cosyne Abstracts, 2019, Lisbon, Portugal., 2019 | | 2019 |
Philipp BerensHertie Institute for AI in Brain Health, University of TübingenE-mail confirmado em uni-tuebingen.de