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ORCIDFabian H. Sinz
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- affiliation: University of Tübingen, Institute for Neurobiology, Germany
- affiliation: Max Planck Institute for Biological Cybernetics, Tübingen, Germany
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2020 – today
- 2024
[i10]Pawel A. Pierzchlewicz, Caio da Silva, R. James Cotton, Fabian H. Sinz:
Platypose: Calibrated Zero-Shot Multi-Hypothesis 3D Human Motion Estimation. CoRR abs/2403.06164 (2024)- 2023
- [c25]Konstantin-Klemens Lurz, Mohammad Bashiri, Edgar Y. Walker, Fabian H. Sinz:
Bayesian Oracle for bounding information gain in neural encoding models. ICLR 2023 - [c24]Pawel A. Pierzchlewicz, Mohammad Bashiri, R. James Cotton, Fabian H. Sinz:
Optimizing MPJPE promotes miscalibration in multi-hypothesis human pose lifting. Tiny Papers @ ICLR 2023 - [c23]Pawel A. Pierzchlewicz, Konstantin Willeke, Arne Nix, Pavithra Elumalai, Kelli Restivo, Tori Shinn, Cate Nealley, Gabrielle Rodriguez, Saumil S. Patel, Katrin Franke, Andreas S. Tolias, Fabian H. Sinz:
Energy Guided Diffusion for Generating Neurally Exciting Images. NeurIPS 2023 - [c22]Suhas Shrinivasan, Konstantin-Klemens Lurz, Kelli Restivo, George H. Denfield, Andreas S. Tolias, Edgar Y. Walker, Fabian H. Sinz:
Taking the neural sampling code very seriously: A data-driven approach for evaluating generative models of the visual system. NeurIPS 2023 - [i9]Arne F. Nix, Max F. Burg, Fabian H. Sinz:
HARD: Hard Augmentations for Robust Distillation. CoRR abs/2305.14890 (2023) - 2022
- [c21]Arne Nix, Suhas Shrinivasan, Edgar Y. Walker, Fabian H. Sinz:
Can Functional Transfer Methods Capture Simple Inductive Biases? AISTATS 2022: 10703-10717 - [c20]Luca Baroni
, Mohammad Bashiri, Konstantin F. Willeke, Ján Antolík, Fabian H. Sinz:
Learning invariance manifolds of visual sensory neurons. NeurReps 2022: 301-326 - [i8]Konstantin F. Willeke, Paul G. Fahey, Mohammad Bashiri, Laura Pede, Max F. Burg, Christoph Blessing, Santiago A. Cadena, Zhiwei Ding, Konstantin-Klemens Lurz, Kayla Ponder, Taliah Muhammad, Saumil S. Patel, Alexander S. Ecker, Andreas S. Tolias, Fabian H. Sinz:
The Sensorium competition on predicting large-scale mouse primary visual cortex activity. CoRR abs/2206.08666 (2022) - [i7]Pawel A. Pierzchlewicz, R. James Cotton, Mohammad Bashiri, Fabian H. Sinz:
Multi-hypothesis 3D human pose estimation metrics favor miscalibrated distributions. CoRR abs/2210.11179 (2022) - 2021
- [c19]Konstantin-Klemens Lurz, Mohammad Bashiri, Konstantin Willeke, Akshay Kumar Jagadish, Eric Wang, Edgar Y. Walker, Santiago A. Cadena, Taliah Muhammad, Erick Cobos, Andreas S. Tolias, Alexander S. Ecker, Fabian H. Sinz:
Generalization in data-driven models of primary visual cortex. ICLR 2021 - [c18]Konstantin F. Willeke, Paul G. Fahey, Mohammad Bashiri, Laura Hansel, Christoph Blessing, Konstantin-Klemens Lurz, Max F. Burg, Santiago A. Cadena, Zhiwei Ding, Kayla Ponder, Taliah Muhammad, Saumil S. Patel, Kaiwen Deng, Yuanfang Guan, Yiqin Zhu, Kaiwen Xiao, Xiao Han, Simone Azeglio, Ulisse Ferrari, Peter Neri, Olivier Marre, Adrian Hoffmann, Kirill Fedyanin, Kirill Vishniakov, Maxim Panov, Subash Prakash, Kishan Naik, Kantharaju Narayanappa, Alexander S. Ecker, Andreas S. Tolias, Fabian H. Sinz:
Retrospective on the SENSORIUM 2022 competition. NeurIPS (Competition and Demos) 2021: 314-333 - [c17]Shahd Safarani, Arne Nix, Konstantin Willeke, Santiago A. Cadena, Kelli Restivo, George H. Denfield, Andreas S. Tolias, Fabian H. Sinz:
Towards robust vision by multi-task learning on monkey visual cortex. NeurIPS 2021: 739-751 - [c16]Mohammad Bashiri, Edgar Y. Walker, Konstantin-Klemens Lurz, Akshay Kumar Jagadish, Taliah Muhammad, Zhiwei Ding, Zhuokun Ding, Andreas S. Tolias, Fabian H. Sinz:
A flow-based latent state generative model of neural population responses to natural images. NeurIPS 2021: 15801-15815 - [i6]Shahd Safarani, Arne Nix, Konstantin Willeke, Santiago A. Cadena, Kelli Restivo, George H. Denfield, Andreas S. Tolias, Fabian H. Sinz:
Towards robust vision by multi-task learning on monkey visual cortex. CoRR abs/2107.14344 (2021) - 2020
- [c15]Ivan Ustyuzhaninov, Santiago A. Cadena, Emmanouil Froudarakis, Paul G. Fahey, Edgar Y. Walker, Erick Cobos, Jacob Reimer, Fabian H. Sinz, Andreas S. Tolias, Matthias Bethge, Alexander S. Ecker:
Rotation-invariant clustering of neuronal responses in primary visual cortex. ICLR 2020 - [c14]R. James Cotton, Fabian H. Sinz, Andreas S. Tolias:
Factorized Neural Processes for Neural Processes: K-Shot Prediction of Neural Responses. NeurIPS 2020 - [i5]R. James Cotton, Fabian H. Sinz, Andreas S. Tolias:
Factorized Neural Processes for Neural Processes: $K$-Shot Prediction of Neural Responses. CoRR abs/2010.11810 (2020)
2010 – 2019
- 2019
- [c13]Alexander S. Ecker, Fabian H. Sinz, Emmanouil Froudarakis, Paul G. Fahey, Santiago A. Cadena, Edgar Y. Walker, Erick Cobos, Jacob Reimer, Andreas S. Tolias, Matthias Bethge:
A rotation-equivariant convolutional neural network model of primary visual cortex. ICLR (Poster) 2019 - [c12]Zhe Li, Wieland Brendel, Edgar Y. Walker, Erick Cobos, Taliah Muhammad, Jacob Reimer, Matthias Bethge, Fabian H. Sinz, Xaq Pitkow, Andreas S. Tolias:
Learning from brains how to regularize machines. NeurIPS 2019: 9525-9535 - [i4]Zhe Li, Wieland Brendel, Edgar Y. Walker, Erick Cobos, Taliah Muhammad, Jacob Reimer, Matthias Bethge, Fabian H. Sinz, Xaq Pitkow, Andreas S. Tolias:
Learning From Brains How to Regularize Machines. CoRR abs/1911.05072 (2019) - 2018
- [c11]Fabian H. Sinz, Alexander S. Ecker, Paul G. Fahey, Edgar Y. Walker, Erick Cobos, Emmanouil Froudarakis, Dimitri Yatsenko, Xaq Pitkow, Jacob Reimer, Andreas S. Tolias:
Stimulus domain transfer in recurrent models for large scale cortical population prediction on video. NeurIPS 2018: 7199-7210 - [i3]Alexander S. Ecker, Fabian H. Sinz, Emmanouil Froudarakis, Paul G. Fahey, Santiago A. Cadena, Edgar Y. Walker, Erick Cobos, Jacob Reimer, Andreas S. Tolias, Matthias Bethge:
A rotation-equivariant convolutional neural network model of primary visual cortex. CoRR abs/1809.10504 (2018) - 2017
- [c10]Mengye Ren, Renjie Liao, Raquel Urtasun, Fabian H. Sinz, Richard S. Zemel:
Normalizing the Normalizers: Comparing and Extending Network Normalization Schemes. ICLR (Poster) 2017 - 2016
- [i2]Mengye Ren, Renjie Liao, Raquel Urtasun, Fabian H. Sinz, Richard S. Zemel:
Normalizing the Normalizers: Comparing and Extending Network Normalization Schemes. CoRR abs/1611.04520 (2016) - 2013
- [j7]Fabian H. Sinz, Matthias Bethge:
What Is the Limit of Redundancy Reduction with Divisive Normalization? Neural Comput. 25(11): 2809-2814 (2013) - [j6]Fabian H. Sinz, Matthias Bethge:
Temporal Adaptation Enhances Efficient Contrast Gain Control on Natural Images. PLoS Comput. Biol. 9(1) (2013) - [c9]Fabian H. Sinz, Anna Stockl, Jan Grewe, Jan Benda:
Least Informative Dimensions. NIPS 2013: 413-421 - 2012
- [b1]Fabian H. Sinz:
Orientation Selectivity and Contrast Gain Control in Representations of Natural Images (Orientierungsselektivität und Kontrastverstärkungsregelung in Repräsentationen von natürlichen Bildern). Tübingen University, Germany, 2012 - 2011
- [j5]Lucas Theis, Sebastian Gerwinn, Fabian H. Sinz, Matthias Bethge:
In All Likelihood, Deep Belief Is Not Enough. J. Mach. Learn. Res. 12: 3071-3096 (2011) - 2010
- [j4]Fabian H. Sinz, Matthias Bethge:
Lp-Nested Symmetric Distributions. J. Mach. Learn. Res. 11: 3409-3451 (2010) - [i1]Lucas Theis, Sebastian Gerwinn, Fabian H. Sinz, Matthias Bethge:
In All Likelihood, Deep Belief Is Not Enough. CoRR abs/1011.6086 (2010)
2000 – 2009
- 2009
- [j3]Fabian H. Sinz, Sebastian Gerwinn, Matthias Bethge:
Characterization of the p-generalized normal distribution. J. Multivar. Anal. 100(5): 817-820 (2009) - [j2]Jan Eichhorn, Fabian H. Sinz, Matthias Bethge:
Natural Image Coding in V1: How Much Use Is Orientation Selectivity? PLoS Comput. Biol. 5(4) (2009) - [c8]Fabian H. Sinz, Eero P. Simoncelli, Matthias Bethge:
Hierarchical Modeling of Local Image Features through $L_p$-Nested Symmetric Distributions. NIPS 2009: 1696-1704 - 2008
- [c7]Fabian H. Sinz, Matthias Bethge:
The Conjoint Effect of Divisive Normalization and Orientation Selectivity on Redundancy Reduction. NIPS 2008: 1521-1528 - 2007
- [c6]Fabian H. Sinz, Olivier Chapelle, Alekh Agarwal, Bernhard Schölkopf:
An Analysis of Inference with the Universum. NIPS 2007: 1369-1376 - 2006
- [j1]Ronan Collobert, Fabian H. Sinz, Jason Weston, Léon Bottou:
Large Scale Transductive SVMs. J. Mach. Learn. Res. 7: 1687-1712 (2006) - [c5]Ronan Collobert, Fabian H. Sinz, Jason Weston, Léon Bottou:
Trading convexity for scalability. ICML 2006: 201-208 - [c4]Jason Weston, Ronan Collobert, Fabian H. Sinz, Léon Bottou, Vladimir Vapnik:
Inference with the Universum. ICML 2006: 1009-1016 - 2005
- [c3]Joaquin Quiñonero Candela, Carl Edward Rasmussen, Fabian H. Sinz, Olivier Bousquet, Bernhard Schölkopf:
Evaluating Predictive Uncertainty Challenge. MLCW 2005: 1-27 - 2004
- [c2]Fabian H. Sinz, Joaquin Quiñonero Candela, Gökhan H. Bakir, Carl Edward Rasmussen, Matthias O. Franz:
Learning Depth from Stereo. DAGM-Symposium 2004: 245-252 - [c1]Dilan Görür, Carl Edward Rasmussen, Andreas S. Tolias, Fabian H. Sinz, Nikos K. Logothetis:
Modelling Spikes with Mixtures of Factor Analysers. DAGM-Symposium 2004: 391-398
Coauthor Index
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