Unpublished Preprints:
*lab members names in bold font.
SuperAnimal models pretrained for plug-and-play analysis of animal behavior. Shaokai Ye, Anastasiia Filippova, Jessy Lauer, Maxime Vidal, Steffen Schneider, Tian Qiu, Alexander Mathis, Mackenzie Weygandt Mathis*
Keypoint-MoSeq: parsing behavior by linking point tracking to pose dynamics. Caleb Weinreb , Mohammed Abdal Monium Osman, Libby Zhang, Sherry Lin , Jonah Pearl , Sidharth Annapragada, Eli Conlin, Winthrop F. Gillis, Maya Jay, Shaokai Ye, Alexander Mathis, Mackenzie Weygandt Mathis, Talmo Pereira , Scott W. Linderman,* and Sandeep Robert Datta*
Now Published Preprints:
AmadeusGPT: a natural language interface for interactive animal behavioral analysis. Shaokai Ye, Jessy Lauer, Mu Zhou, Alexander Mathis, Mackenzie W. Mathis* —> now accepted at NeurIPS2023!
Rethinking pose estimation in crowds: overcoming the detection information-bottleneck and ambiguity. Mu Zhou, Lucas Stoffl, Mackenzie Mathis, Alexander Mathis. arXiv:2306.07879 —> now accepted to ICCV2023
Contrasting action and posture coding with hierarchical deep neural network models of proprioception. Kai J. Sandbrink, Pranav Mamidanna, Claudio Michaelis, Matthias Bethge, Mackenzie Weygandt Mathis*, Alexander Mathis* -> now published in eLife 2023 (legacy system). See project page here: https://www.mathislab.org/deepdraw
Learnable latent embeddings for joint behavioral and neural analysis. Steffen Schneider*, Jin Hwa Lee* and Mackenzie Weygandt Mathis. arXiv:abs/2204.00673 2022 -> published in Nature 2023.
Striatal dopamine explains novelty-induced behavioral dynamics and individual variability in threat prediction. Korleki Akiti, Iku Tsutsui-Kimura, Yudi Xie, Alexander Mathis, Jeffrey Markowitz, Rockwell Anyoha, Sandeep Robert Datta, Mackenzie Weygandt Mathis, Naoshige Uchida, Mitsuko Watabe-Uchida. BioRxiv 2021. Now published in Neuron 2022
Multi-animal pose estimation and tracking with DeepLabCut.
Jessy Lauer, Mu Zhou, Shaokai Ye, William Menegas, Tanmay Nath, Mohammed Mostafizur Rahman, Valentina Di Santo, Daniel Soberanes, Guoping Feng, Venkatesh N Murthy, George Lauder, Catherine Dulac, Mackenzie W Mathis*, Alexander Mathis* (co-senior) bioRxiv 2021 Now published in Nature Methods 2022
Seeing biodiversity: perspectives in machine learning for wildlife conservation. Devis Tuia, Benjamin Kellenberger, Sara Beery, Blair R Costelloe, Silvia Zuffi, Benjamin Risse, Alexander Mathis, Mackenzie W Mathis, Frank van Langevelde, Tilo Burghardt, Roland Kays, Holger Klinck, Martin Wikelski, Iain D Couzin, Grant van Horn, Margaret C Crofoot, Charles V Stewart, Tanya Berger-Wolf. arXiv 2021. Now published in Nature Communications 2022
AcinoSet: A 3D Pose Estimation Dataset and Baseline Models for Cheetahs in the Wild.
Daniel Joska, Liam Clark, Naoya Muramatsu, Ricardo Jericevich, Fred Nicolls, Alexander Mathis, Mackenzie W. Mathis & Amir Patel. Arxiv 2021. Now published in IEEE International Conference on Robotics and Automation (ICRA) 2021
Measuring and modeling the motor system with machine learning.
Sébastien B. Hausmann, Alessandro Marin Vargas, Alexander Mathis, Mackenzie W. Mathis. Arxiv 2021. Now published in Current Opinion in Neurobiology 2021
Dynamic extrinsic pacing of the HOX clock in human axial progenitors controls motor neuron subtype specification.
Vincent Mouilleau,Célia Vaslin, Simona Gribaudo, Rémi Robert,Nour Nicolas, Margot Jarrige, Angélique Terray, Léa Lesueur, Mackenzie W. Mathis, Gist Croft, Mathieu Daynac, Virginie RouillerFabre, Hynek Wichterle,Vanessa Ribes, Cécile Martinat, Stéphane Nedelec. BioRxiv 2020. Published in Development 2021
Real-time, low-latency closed-loop feedback using markerless posture tracking.
Gary Kane, Gonçalo Lopes, Jonny L. Saunders, Alexander Mathis, Mackenzie W. Mathis. bioRxiv 2020.08.04.236422; doi | code | benchmarking website. Published at eLife 2020
Pretraining boosts out-of-domain robustness for pose estimation. Alexander Mathis, Thomas Biasi, Steffen Schneider, Mert Yüksekgönül, Byron Rogers, Matthias Bethge, Mackenzie W. Mathis. arXiv v1: 2019
short form presented at ICML 2020 Uncertainty & Robustness in Deep Learning Workshop & Published at WACV 2021
A Primer on Motion Capture with Deep Learning: Principles, Pitfalls and Perspectives. Alexander Mathis, Steffen Schneider, Jessy Lauer, Mackenzie W. Mathis arXiv:2009.00564v2 [cs.CV] Published in Neuron 2020
Deep learning tools for the measurement of animal behavior in neuroscience
Mackenzie W. Mathis & Alexander Mathis https://arxiv.org/abs/1909.13868. Published in Current Opinion in Neurobiology 2020
Using DeepLabCut for 3D markerless pose estimation across species and behaviors. Tanmay Nath*, Alexander Mathis*, An Chi Chen, Amir Patel, Matthias Bethge, and Mackenzie W. Mathis. BioRxiv. 2018 (submitted 11/21/2018) *co-first authors. Published in Nature Protocols 2019
Markerless tracking of user-defined features with deep learning
Alexander Mathis, Pranav Mamidanna, Taiga Abe, Kevin M. Cury, Venkatesh N. Murthy, Mackenzie Mathis*and Matthias Bethge*. aRxiv (submitted 4/8/2018) *co-senior authors
https://arxiv.org/abs/1804.03142v1 | See our page on DeepLabCut for more info
Published in Nature Neuroscience: https://www.nature.com/articles/s41593-018-0209-y
Selected conference contributions: