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Jan-Matthis Lueckmann
Jan-Matthis Lueckmann
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Title
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Cited by
Year
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
2232017
SBI--A toolkit for simulation-based inference
A Tejero-Cantero, J Boelts, M Deistler, JM Lueckmann, C Durkan, ...
arXiv preprint arXiv:2007.09114, 2020
2112020
Ostracism Online: A social media ostracism paradigm
W Wolf, A Levordashka, JR Ruff, S Kraaijeveld, JM Lueckmann, ...
Behavior Research Methods 47, 361-373, 2015
1972015
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
1762020
Benchmarking Simulation-Based Inference
JM Lueckmann, J Boelts, DS Greenberg, PJ Gonçalves, JH Macke
Proceedings of The 24th International Conference on Artificial Intelligence …, 2021
1522021
Likelihood-free inference with emulator networks
JM Lueckmann, G Bassetto, T Karaletsos, JH Macke
Proceedings of Machine Learning Research 96, 32–53, 2019
1212019
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
462018
Flexible and efficient simulation-based inference for models of decision-making
J Boelts, JM Lueckmann, R Gao, JH Macke
Elife 11, e77220, 2022
292022
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
262022
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
182020
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
182016
Advances in Neural Information Processing Systems
JM Lueckmann, PJ Goncalves, G Bassetto, K Öcal, M Nonnenmacher, ...
Go to reference in article, 2017
142017
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
JM Lueckmann, G Bassetto, T Karaletsos, JH Macke
arXiv preprint arXiv:1805.09294, 2018
92018
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
Simulation-Based Inference for Neuroscience and Beyond
JM Lückmann
Universität Tübingen, 2022
32022
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
Robust statistical inference for simulation-based models in neuroscience
M Nonnenmacher, PJ Goncalves, G Bassetto, JM Lueckmann, JH Macke
Bernstein Conference 2018, Berlin, Germany, 2018
22018
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Articles 1–20