733 citations · 2.2k across the 19 of their papers we have counts for
20 papers
Extracting Governing Equations from Latent Dynamics via Multi-View Contrastive Learning
Paolo Muratore, Mackenzie Weygandt Mathis
Identifying latent dynamical systems from noisy, high-dimensional measurements is a central problem at the intersection of representation learning, system identification, and scien…
PRIMA: Boosting Animal Mesh Recovery with Biological Priors and Test-Time Adaptation
Xiaohang Yu, Ti Wang, Mackenzie Weygandt Mathis
We present PRIMA (*PRI*ors for *M*esh *A*daptation), a framework for robust 3D quadruped mesh recovery under severe species and pose imbalance. Existing animal reconstruction metho…
FMPose3D: monocular 3D pose estimation via flow matching
Ti Wang, Xiaohang Yu, Mackenzie Weygandt Mathis
Monocular 3D pose estimation is fundamentally ill-posed due to depth ambiguity and occlusions, thereby motivating probabilistic methods that generate multiple plausible 3D pose hyp…
DISTIL: Data-Free Inversion of Suspicious Trojan Inputs via Latent Diffusion
Hossein Mirzaei, Zeinab Taghavi, Sepehr Rezaee +3
Deep neural networks have demonstrated remarkable success across numerous tasks, yet they remain vulnerable to Trojan (backdoor) attacks, raising serious concerns about their safet…
LLaVAction: evaluating and training multi-modal large language models for action understanding
Haozhe Qi, Shaokai Ye, Alexander Mathis +1
Understanding human behavior requires measuring behavioral actions. Due to its complexity, behavior is best mapped onto a rich, semantic structure such as language. Emerging multim…
Time-series attribution maps with regularized contrastive learning
Steffen Schneider, Rodrigo González Laiz, Anastasiia Filippova +2
Gradient-based attribution methods aim to explain decisions of deep learning models but so far lack identifiability guarantees. Here, we propose a method to generate attribution ma…