1 code implementation • CVPR 2023 • Jennifer J. Sun, Lili Karashchuk, Amil Dravid, Serim Ryou, Sonia Fereidooni, John Tuthill, Aggelos Katsaggelos, Bingni W. Brunton, Georgia Gkioxari, Ann Kennedy, Yisong Yue, Pietro Perona
In this way, we discover keypoints without requiring manual supervision in videos of humans and rats, demonstrating the potential of 3D keypoint discovery for studying behavior.
no code implementations • 7 Sep 2022 • Richard Gast, Sara A. Solla, Ann Kennedy
The Izhikevich single neuron model can account for a broad range of different neuron types and spiking patterns, thus rendering it an optimal candidate for a mean-field theoretic treatment of brain dynamics in heterogeneous networks.
1 code implementation • 21 Jul 2022 • Jennifer J. Sun, Markus Marks, Andrew Ulmer, Dipam Chakraborty, Brian Geuther, Edward Hayes, Heng Jia, Vivek Kumar, Sebastian Oleszko, Zachary Partridge, Milan Peelman, Alice Robie, Catherine E. Schretter, Keith Sheppard, Chao Sun, Param Uttarwar, Julian M. Wagner, Eric Werner, Joseph Parker, Pietro Perona, Yisong Yue, Kristin Branson, Ann Kennedy
We introduce MABe22, a large-scale, multi-agent video and trajectory benchmark to assess the quality of learned behavior representations.
no code implementations • 17 Jun 2022 • Richard Gast, Sara A. Solla, Ann Kennedy
The brain is composed of complex networks of interacting neurons that express considerable heterogeneity in their physiology and spiking characteristics.
1 code implementation • CVPR 2022 • Jennifer J. Sun, Serim Ryou, Roni Goldshmid, Brandon Weissbourd, John Dabiri, David J. Anderson, Ann Kennedy, Yisong Yue, Pietro Perona
We propose a method for learning the posture and structure of agents from unlabelled behavioral videos.
Ranked #1 on Unsupervised Human Pose Estimation on Human3.6M
1 code implementation • 28 Jul 2021 • Eric Zhan, Jennifer J. Sun, Ann Kennedy, Yisong Yue, Swarat Chaudhuri
We present a framework for the unsupervised learning of neurosymbolic encoders, which are encoders obtained by composing neural networks with symbolic programs from a domain-specific language.
no code implementations • 11 Jun 2021 • Megan Tjandrasuwita, Jennifer J. Sun, Ann Kennedy, Swarat Chaudhuri, Yisong Yue
Hand-annotated data can vary due to factors such as subjective differences, intra-rater variability, and differing annotator expertise.
1 code implementation • 6 Apr 2021 • Jennifer J. Sun, Tomomi Karigo, Dipam Chakraborty, Sharada P. Mohanty, Benjamin Wild, Quan Sun, Chen Chen, David J. Anderson, Pietro Perona, Yisong Yue, Ann Kennedy
Multi-agent behavior modeling aims to understand the interactions that occur between agents.
1 code implementation • CVPR 2021 • Jennifer J. Sun, Ann Kennedy, Eric Zhan, David J. Anderson, Yisong Yue, Pietro Perona
The tasks in our method can be efficiently engineered by domain experts through a process we call "task programming", which uses programs to explicitly encode structured knowledge from domain experts.