Pawel Pierzchlewicz

Graduate Student

neuroscience pose
Pawel Pierzchlewicz

Deep neural networks (DNNs) have repeatedly proven to be successful in modelling complex functions. However, they are known to be data-hungry; as a result, they are often difficult to apply in scenarios where large datasets are not available. Additionally, DNNs are prone to break world governing laws (e.g. physics) in areas like pose estimation. This may be due to the model-free nature of DNNs. Having to learn how the world works from scratch may result in data hungriness and an incorrect world model. My goal is to construct model-based DNNs to obtain greater data efficiency and robustness. Since probabilistic modelling provides a language for describing structural relationships, I intend to utilise it to achieve model-based DNNs. In particular, my goal is to apply these model-based methods to 3D pose estimation for freely moving animals.

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2024

Jiakun Fu, Suhas Shrinivasan, Luca Baroni, Zhuokun Ding, Paul G. Fahey, Paweł Pierzchlewicz, Kayla Ponder, Rachel Froebe, Lydia Ntanavara, Taliah Muhammad, Konstantin F Willeke, Eric Wang, Zhiwei Ding, Dat T. Tran, Stelios Papadopoulos, Saumil Patel, Jacob Reimer, Alexander S. Ecker, Xaq Pitkow, Jan Antolik, Fabian H. Sinz, Ralf M. Haefner, Andreas S. Tolias, Katrin Franke Pattern completion and disruption characterize contextual modulation in the visual cortex bioRxiv
Jiakun Fu, Pawel A. Pierzchlewicz, Konstantin F. Willeke, Mohammad Bashiri, Taliah Muhammad, Maria Diamantaki, Emmanouil Froudarakis, Kelli Restivo, Kayla Ponder, George H. Denfield, Fabian H. Sinz, Andreas S. Tolias, Katrin Franke Heterogeneous orientation tuning in primary visual cortex of mice diverges from Gabor-like receptive fields in primates Cell Reports
Pawel A. Pierzchlewicz, Caio da Silva, James Cotton, Fabian H. Sinz Platypose: Calibrated Zero-Shot Multi-Hypothesis 3D Human Motion Estimation arXiv

2023

Pawel A. Pierzchlewicz, Konstantin F. Willeke, Arne F. Nix, Pavithra Elumalai, Kelli Restivo, Tori Shinn, Cate Nealley, Gabrielle Rodriguez, Saumil Patel, Katrin Franke, Andreas S. Tolias, Fabian H. Sinz Energy Guided Diffusion for Generating Neurally Exciting Images NeurIPS
Paweł A. Pierzchlewicz, Mohammad Bashiri, R. James Cotton, Fabian H. Sinz Optimizing MPJPE promotes miscalibration in multi-hypothesis human pose lifting ICLR - tiny paper
conference paper · pose · openreview

2022

Paweł A. Pierzchlewicz, R. James Cotton, Mohammad Bashiri, Fabian H. Sinz Multi-hypothesis 3D human pose estimation metrics favor miscalibrated distributions arXiv
preprint · pose · arXiv