2.3k citations · 2.5k across the 9 of their papers we have counts for
4 papers · 1 filter
Leveraging Large (Visual) Language Models for Robot 3D Scene Understanding
William Chen, Siyi Hu, Rajat Talak +1
Abstract semantic 3D scene understanding is a problem of critical importance in robotics. As robots still lack the common-sense knowledge about household objects and locations of a…
Self-Supervised Learning of Brain Dynamics from Broad Neuroimaging Data
Armin W. Thomas, Christopher Ré, Russell A. Poldrack
Self-supervised learning techniques are celebrating immense success in natural language processing (NLP) by enabling models to learn from broad language data at unprecedented scale…
Differentiable programming for functional connectomics
Rastko Ciric, Armin W. Thomas, Oscar Esteban +1
Mapping the functional connectome has the potential to uncover key insights into brain organisation. However, existing workflows for functional connectomics are limited in their ad…
Comparing interpretation methods in mental state decoding analyses with deep learning models
Armin W. Thomas, Christopher Ré, Russell A. Poldrack
Deep learning (DL) models find increasing application in mental state decoding, where researchers seek to understand the mapping between mental states (e.g., perceiving fear or joy…