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…
A Contrastive Teacher-Student Framework for Novelty Detection under Style Shifts
Hossein Mirzaei, Mojtaba Nafez, Moein Madadi +12
There have been several efforts to improve Novelty Detection (ND) performance. However, ND methods often suffer significant performance drops under minor distribution shifts caused…
Adaptive Intelligence: leveraging insights from adaptive behavior in animals to build flexible AI systems
Mackenzie Weygandt Mathis
Biological intelligence is inherently adaptive -- animals continually adjust their actions based on environmental feedback. However, creating adaptive artificial intelligence (AI)…
Adversarially Robust Out-of-Distribution Detection Using Lyapunov-Stabilized Embeddings
Hossein Mirzaei, Mackenzie W. Mathis
Despite significant advancements in out-of-distribution (OOD) detection, existing methods still struggle to maintain robustness against adversarial attacks, compromising their reli…
AmadeusGPT: a natural language interface for interactive animal behavioral analysis
Shaokai Ye, Jessy Lauer, Mu Zhou +2
The process of quantifying and analyzing animal behavior involves translating the naturally occurring descriptive language of their actions into machine-readable code. Yet, codifyi…
Rethinking pose estimation in crowds: overcoming the detection information-bottleneck and ambiguity
Mu Zhou, Lucas Stoffl, Mackenzie Weygandt Mathis +1
Frequent interactions between individuals are a fundamental challenge for pose estimation algorithms. Current pipelines either use an object detector together with a pose estimator…
Learnable latent embeddings for joint behavioral and neural analysis
Steffen Schneider, Jin Hwa Lee, Mackenzie Weygandt Mathis
Mapping behavioral actions to neural activity is a fundamental goal of neuroscience. As our ability to record large neural and behavioral data increases, there is growing interest…
SuperAnimal pretrained pose estimation models for behavioral analysis
Shaokai Ye, Anastasiia Filippova, Jessy Lauer +5
Quantification of behavior is critical in applications ranging from neuroscience, veterinary medicine and animal conservation efforts. A common key step for behavioral analysis is…
Seeing biodiversity: perspectives in machine learning for wildlife conservation
Devis Tuia, Benjamin Kellenberger, Sara Beery +15
Data acquisition in animal ecology is rapidly accelerating due to inexpensive and accessible sensors such as smartphones, drones, satellites, audio recorders and bio-logging device…
AcinoSet: A 3D Pose Estimation Dataset and Baseline Models for Cheetahs in the Wild
Daniel Joska, Liam Clark, Naoya Muramatsu +5
Animals are capable of extreme agility, yet understanding their complex dynamics, which have ecological, biomechanical and evolutionary implications, remains challenging. Being abl…
Measuring and modeling the motor system with machine learning
Sébastien B. Hausmann, Alessandro Marin Vargas, Alexander Mathis +1
The utility of machine learning in understanding the motor system is promising a revolution in how to collect, measure, and analyze data. The field of movement science already eleg…
A Primer on Motion Capture with Deep Learning: Principles, Pitfalls and Perspectives
Alexander Mathis, Steffen Schneider, Jessy Lauer +1
Extracting behavioral measurements non-invasively from video is stymied by the fact that it is a hard computational problem. Recent advances in deep learning have tremendously adva…
Deep learning tools for the measurement of animal behavior in neuroscience
Mackenzie W. Mathis, Alexander Mathis
Recent advances in computer vision have made accurate, fast and robust measurement of animal behavior a reality. In the past years powerful tools specifically designed to aid the m…
Pretraining boosts out-of-domain robustness for pose estimation
Alexander Mathis, Thomas Biasi, Steffen Schneider +4
Neural networks are highly effective tools for pose estimation. However, as in other computer vision tasks, robustness to out-of-domain data remains a challenge, especially for sma…
Markerless tracking of user-defined features with deep learning
Alexander Mathis, Pranav Mamidanna, Taiga Abe +4
Quantifying behavior is crucial for many applications in neuroscience. Videography provides easy methods for the observation and recording of animal behavior in diverse settings, y…