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Jan-Matthis Lueckmann
Jan-Matthis Lueckmann
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Cited by
Year
SBI--A toolkit for simulation-based inference
A Tejero-Cantero, J Boelts, M Deistler, JM Lueckmann, C Durkan, ...
arXiv preprint arXiv:2007.09114, 2020
2812020
Flexible statistical inference for mechanistic models of neural dynamics
JM Lueckmann, PJ Goncalves, G Bassetto, K Öcal, M Nonnenmacher, ...
Advances in neural information processing systems 30, 2017
2782017
Ostracism Online: A social media ostracism paradigm
W Wolf, A Levordashka, JR Ruff, S Kraaijeveld, JM Lueckmann, ...
Behavior Research Methods 47, 361-373, 2015
2232015
Training deep neural density estimators to identify mechanistic models of neural dynamics
PJ Gonçalves, JM Lueckmann, M Deistler, M Nonnenmacher, K Öcal, ...
Elife 9, e56261, 2020
2162020
Benchmarking Simulation-Based Inference
JM Lueckmann, J Boelts, DS Greenberg, PJ Gonçalves, JH Macke
Proceedings of The 24th International Conference on Artificial Intelligence …, 2021
1962021
Likelihood-free inference with emulator networks
JM Lueckmann, G Bassetto, T Karaletsos, JH Macke
Proceedings of Machine Learning Research 96, 32–53, 2019
1362019
p53 Regulates the neuronal intrinsic and extrinsic responses affecting the recovery of motor function following spinal cord injury
EM Floriddia, KI Rathore, A Tedeschi, G Quadrato, A Wuttke, ...
Journal of Neuroscience 32 (40), 13956-13970, 2012
602012
Can serial dependencies in choices and neural activity explain choice probabilities?
JM Lueckmann, JH Macke, H Nienborg
Journal of Neuroscience 38 (14), 3495-3506, 2018
512018
Flexible and efficient simulation-based inference for models of decision-making
J Boelts, JM Lueckmann, R Gao, JH Macke
Elife 11, e77220, 2022
492022
GATSBI: Generative adversarial training for simulation-based inference
P Ramesh, JM Lueckmann, J Boelts, Á Tejero-Cantero, DS Greenberg, ...
arXiv preprint arXiv:2203.06481, 2022
352022
Pre-stimulus phase and amplitude regulation of phase-locked responses are maximized in the critical state
AE Avramiea, R Hardstone, JM Lueckmann, J Bím, HD Mansvelder, ...
Elife 9, e53016, 2020
252020
Proceedings of The 24th International Conference on Artificial Intelligence and Statistics
JM Lueckmann, J Boelts, D Greenberg, P Goncalves, J Macke, ...
PMLR, 2021
202021
Spatiotemporal dynamics of random stimuli account for trial-to-trial variability in perceptual decision making
H Park, JM Lueckmann, K von Kriegstein, S Bitzer, SJ Kiebel
Scientific reports 6 (1), 18832, 2016
192016
Advances in Neural Information Processing Systems
JM Lueckmann, PJ Goncalves, G Bassetto, K Öcal, M Nonnenmacher, ...
Go to reference in article, 2017
132017
Training deep neural density estimators to identify mechanistic models of neural dynamics. bioRxiv
PJ Gonçalves, JM Lueckmann, M Deistler, M Nonnenmacher, K Öcal, ...
122019
Likelihood-free inference with emulator networks. arxiv e-prints
J Lueckmann, G Bassetto, T Karaletsos, J Macke
arXiv preprint arXiv:1805.09294, 2019
102019
Simulation-based inference for neuroscience and beyond
JM Lückmann
Universität Tübingen, 2022
52022
Comparing neural simulations by neural density estimation
J Boelts, JM Lueckmann, PJ Goncalves, H Sprekeler, JH Macke
2019 Conference on Cognitive Computational Neuroscience. Berlin, Germany …, 2019
52019
Flexible statistical inference for mechanistic models of neural dynamics. arXiv
JM Lueckmann, PJ Goncalves, G Bassetto, K Ocal, M Nonnenmacher, ...
arXiv preprint arXiv:1711.01861, 2017
52017
Statistical inference for analyzing sloppiness in neuroscience models
M Deistler, GJ Pedro, JM Lueckmann, K Oecal, DS Greenberg, JH Macke
Bernstein Conference 2019, Berlin, Germany, 2019
22019
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Articles 1–20