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Jan-Matthis Lueckmann

sbi: A toolkit for simulation-based inference
2020 · Alvaro Tejero-Cantero, Jan Boelts, et al. · The Journal of Open Source Software · 301
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Training deep neural density estimators to identify mechanistic models of neural dynamics
2020 · Pedro J. Gonçalves, Jan-Matthis Lueckmann, et al. · eLife · 241
Ostracism Online: A social media ostracism paradigm
2014 · Wouter Wolf, Ana Levordashka, et al. · Behavior Research Methods · 212
Flexible statistical inference for mechanistic models of neural dynamics
2017 · Lueckmann, Jan-Matthis, Goncalves, Pedro J., et al. · Lirias · 136
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Likelihood-free inference with emulator networks
2018 · Lueckmann, Jan-Matthis, Bassetto, Giacomo, et al. · arXiv (Cornell University) · 76
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Benchmarking Simulation-Based Inference
2021 · Lueckmann, Jan-Matthis, Boelts, Jan, et al. · arXiv (Cornell University) · 74
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p53 Regulates the Neuronal Intrinsic and Extrinsic Responses Affecting the Recovery of Motor Function following Spinal Cord Injury
2012 · Elisa M. Floriddia, Khizr I. Rathore, et al. · Journal of Neuroscience · 53
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Flexible and efficient simulation-based inference for models of decision-making
2022 · Jan Boelts, Jan-Matthis Lueckmann, et al. · eLife · 50
Can Serial Dependencies in Choices and Neural Activity Explain Choice Probabilities?
2018 · Jan-Matthis Lueckmann, Jakob H. Macke, et al. · Journal of Neuroscience · 39
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Pre-stimulus phase and amplitude regulation of phase-locked responses are maximized in the critical state
2020 · Arthur-Ervin Avramiea, Richard Hardstone, et al. · eLife · 29
sbi reloaded: a toolkit for simulation-based inference workflows
2025 · Jan Boelts, Michael Deistler, et al. · The Journal of Open Source Software · 26
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An AI system to help scientists write expert-level empirical software
2026 · Eser Aygün, Anastasiya Belyaeva, et al. · Nature · 17
Spatiotemporal dynamics of random stimuli account for trial-to-trial variability in perceptual decision making
2016 · Hame Park, Jan-Matthis Lueckmann, et al. · Scientific Reports · 16
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GATSBI: Generative Adversarial Training for Simulation-Based Inference
2022 · Ramesh, Poornima, Lueckmann, Jan-Matthis, et al. · Lirias · 5
Simulation-Based Inference: A Practical Guide
2025 · Deistler, Michael, Boelts, Jan, et al. · HAL · 4
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ZAPBench: A Benchmark for Whole-Brain Activity Prediction in Zebrafish
2025 · Lueckmann, Jan-Matthis, Immer, Alexander, et al. · arXiv (Cornell University) · 2
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Comparing neural simulations by neural density estimation
2019 · Jan Boelts, Jan-Matthis Lueckmann, et al. · Conference on Cognitive Computational Neuroscience (CCN) · 2
sbi reloaded: a toolkit for simulation-based inference workflows
2024 · Boelts, Jan, Deistler, Michael, et al. · arXiv (Cornell University) · 1
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Author response: Training deep neural density estimators to identify mechanistic models of neural dynamics
2020 · Pedro J Gonçalves, Jan-Matthis Lueckmann, et al. · eLife · 1
Discovering Mechanistic Models of Neural Activity: System Identification in an in Silico Zebrafish
2026 · Lueckmann, Jan-Matthis, Jain, Viren, et al. · arXiv (Cornell University)
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An ion channel omnimodel for standardized biophysical neuron modelling
2025 · Chaitanya Chintaluri, William Podlaski, et al. · bioRxiv (Cold Spring Harbor Laboratory)
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Forecasting Whole-Brain Neuronal Activity from Volumetric Video
2025 · Immer, Alexander, Lueckmann, Jan-Matthis, et al. · arXiv (Cornell University)
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Author response: Flexible and efficient simulation-based inference for models of decision-making
2022 · Jan Boelts, Jan-Matthis Lueckmann, et al. · eLife
Author response: Pre-stimulus phase and amplitude regulation of phase-locked responses are maximized in the critical state
2020 · Arthur-Ervin Avramiea, Richard Hardstone, et al. · eLife
Inferring the parameters of neural simulations from high-dimensional observations
2019 · Nonnenmacher, Marcel, Lueckmann, Jan-Matthis, et al. · MPG.PuRe (Max Planck Society)
Works count: 28
Citation count: 1,285
H-index: 13
I10-index: 13
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