Publications

Joint modelling of brain and behaviour dynamics with artificial intelligence

M. W. Mathis; A. Mathis 

Individual identification of brown bears using pose-aware metric learning

B. Rosenberg; M. Zhou; N. Wolf; M. Mathis; B. P. Harris et al. 

Beyond single neurons: population response geometry in digital twins of mouse visual cortex

D. Liscai; E. Luconi; A. Marin Vargas; A. Sanzeni 

MUSt3R: Multi-view Network for Stereo 3D Reconstruction

Y. Cabon; L. Stoffl; L. Antsfeld; G. Csurka; B. Chidlovskii et al. 

Deep-learning models of the ascending proprioceptive pathway are subject to illusions

A. Perez Rotondo; M. Simos; S. Pigeon; F. David; O. Blanke et al. 

EPFL-Smart-Kitchen-30: Densely annotated cooking dataset with 3D kinematics to challenge video and language models

A. Bonnetto; H. Qi; F. Leong; M. Tashkovska; M. Rad et al. 

EPFL-Smart-Kitchen-30 Annotations and Poses

A. Bonnetto; H. Qi; F. Leong; M. Tashkovska; M. Hamidi Rad et al. 

EPFL-Smart-Kitchen-30 Collected data

A. Bonnetto; H. Qi; F. Leong; M. Tashkovska; M. Hamidi Rad et al. 

MammAlps: A multi-view video behavior monitoring dataset of wild mammals in the Swiss Alps

V. Gabeff; D. Tuia; A. Mathis 

Climbing out of the lab: studying motor planning and coarticulation in the climbing gym

A. Bonnetto; A. Mathis 

Data for Deep-learning models of the ascending proprioceptive pathway are subject to illusions

A. Perez Rotondo; S. Pigeon; F. David; M. Simos; O. Blanke et al. 

MammAlps: A multi-view video behavior monitoring dataset of wild mammals in the Swiss Alps

V. Gabeff; H. Qi; B. Flaherty; G. Sümbül; A. Mathis et al. 

From Pose to Behavior: Advancing Multi-Individual Pose Estimation and Hierarchical Action Segmentation with Transformers

From wild to lab: learning pose, identity and behavior across animals with deep learning

Reverse engineering primate sensorimotor control with machine learning

Musculoskeletal motor control with reinforcement learning

PICLe: Pseudo-Annotations for In-Context Learning in Low-Resource Named Entity Detection

S. Mamooler; S. Montariol; A. Mathis; A. Bosselut 

Decoding the brain: From neural representations to mechanistic models

M. W. Mathis; A. P. Rotondo; E. F. Chang; A. S. Tolias; A. Mathis 

Acquiring musculoskeletal skills with curriculum-based reinforcement learning

A. Chiappa; P. Tano; N. Patel; A. R. L. Ingster; A. Pouget et al. 

Elucidating the Hierarchical Nature of Behavior with Masked Autoencoders (BehaveMAE & Shot7M2)

L. Stoffl; A. Bonnetto; S. D’Ascoli; A. Mathis 

Elucidating the Hierarchical Nature of Behavior with Masked Autoencoders

L. Stoffl; S. d’Ascoli; A. Bonnetto; A. Mathis 

Keypoint-MoSeq: parsing behavior by linking point tracking to pose dynamics

C. Weinreb; J. E. Pearl; S. Lin; M. A. M. Osman; L. Zhang et al. 

SuperAnimal pretrained pose estimation models for behavioral analysis

S. Ye; A. Filippova; S. Schneider; M. Vidal; J. Lauer et al. 

HOISDF: Constraining 3D Hand-Object Pose Estimation with Global Signed Distance Fields: Processed data and trained models

H. Qi; C. Zhao; M. Salzmann; A. Mathis 

WildCLIP: Scene and Animal Attribute Retrieval from Camera Trap Data with Domain-Adapted Vision-Language Models

V. A. G. Gabeff; M. Russwurm; D. Tuia; A. Mathis 

Task-driven neural network models predict neural dynamics of proprioception

A. M. Vargas; A. Bisi; A. S. Chiappa; C. Versteeg; L. E. Miller et al. 

Synthetic data (Part 1) for “HOISDF: Constraining 3D Hand-Object Pose Estimation with Global Signed Distance Fields”

H. Qi; C. Zhao; M. Salzmann; A. Mathis 

Task-driven neural network models predict neural dynamics of proprioception: Neural network model weights

A. Marin Vargas; A. Bisi; A. Chiappa; C. Versteeg; L. E. Miller et al. 

Acquiring musculoskeletal skills with curriculum-based reinforcement learning – model weights

A. Chiappa; P. Tano; N. Patel; A. R. L. Ingster; A. Pouget et al. 

Task-driven neural network models predict neural dynamics of proprioception: Experimental data, activations and predictions of neural network models

A. Marin Vargas; A. Bisi; A. S. Chiappa; C. Versteeg; L. E. Miller et al. 

Task-driven neural network models predict neural dynamics of proprioception: Synthetic muscle spindle datasets

A. Marin Vargas; A. Bisi; A. S. Chiappa; C. Versteeg; L. E. Miller et al. 

Synthetic data (Part 2) for “HOISDF: Constraining 3D Hand-Object Pose Estimation with Global Signed Distance Fields”

H. Qi; C. Zhao; M. Salzmann; A. Mathis 

WildCLIP: Scene and animal attribute retrieval from camera trap data with domain-adapted vision-language models

V. A. G. Gabeff; M. C. Russwurm; D. Tuia; A. Mathis 

HOISDF: Constraining 3D Hand-Object Pose Estimation with Global Signed Distance Fields

H. Qi; C. Zhao; M. Salzmann; A. Mathis 

Data for Contrasting action and posture coding with hierarchical deep neural network models of proprioception

K. Sandbrink; P. Mamidanna; C. Michaelis; M. Bethge; M. Mathis et al. 

AmadeusGPT: a natural language interface for interactive animal behavioral analysis

S. Ye; J. Lauer; M. Zhou; A. Mathis; M. Mathis 

Data Champions Lunch Talks – AI and research data, a new synergy

A. Mathis; S. L. Dürr; G. Barazzetti; R. Castello 

Scene and animal attributes retrieval from camera trap data with domain-adapted language-vision models

V. A. G. Gabeff; M. C. Russwurm; D. Tuia; A. Mathis 

Contrasting action and posture coding with hierarchical deep neural network models of proprioception

K. J. Sandbrink; P. Mamidanna; C. Michaelis; M. Bethge; M. W. Mathis et al. 

NeuroAI: If grid cells are the answer, is path integration the question?

M. Frey; M. W. Mathis; A. Mathis 

Task-driven neural network models predict neural dynamics of proprioception

A. Marin Vargas; A. Bisi; A. Chiappa; C. Versteeg; L. Miller et al. 

Neural and algorithmic bases of odor guided trail following in mice

S. Jayakumar; W. Tong; G. Reddy; A. Mathis; V. N. Murthy 

Rethinking pose estimation in crowds: overcoming the detection information bottleneck and ambiguity

M. Zhou; L. Stoffl; M. Mathis; A. Mathis 

Rethinking Pose Estimation in Crowds: Overcoming the Detection Information Bottleneck and Ambiguity

M. Zhou; L. Stoffl; M. Mathis; A. Mathis 

Striatal dopamine explains novelty-induced behavioral dynamics and individual variability in threat prediction

K. Akiti; I. Tsutsui-Kimura; Y. Xie; A. Mathis; J. E. Markowitz et al. 

Multi-animal pose estimation, identification and tracking with DeepLabCut

J. Lauer; M. Zhou; S. Ye; W. Menegas; S. Schneider et al. 

Perspectives in machine learning for wildlife conservation

D. Tuia; B. Kellenberger; S. Beery; B. R. Costelloe; S. Zuffi et al. 

Perspectives on Individual Animal Identification from Biology and Computer Vision

M. Vidal; N. Wolf; B. Rosenberg; B. P. Harris; A. Mathis 

Measuring and modeling the motor system with machine learning

S. B. Hausmann; A. Marin Vargas; A. Mathis; M. Mathis 

Deep learning tools for the analysis of movement, identity and behavior

A. Mathis