Neural Regression, Representational Similarity, Model Zoology & Neural Taskonomy at Scale in Rodent Visual Cortex. - Colin Conwell; David Mayo; Andrei Barbu; Michael A. Buice; George Alvarez; Boris Katz (NeurIPS, 2021)

On the use of Cortical Magnification and Saccades as Biological Proxies for Data Augmentation. - Binxu Wang; David Mayo; Arturo Deza; Andrei Barbu; Colin Conwell (CoRR, 2021)

Testing Relational Understanding in Text-Guided Image Generation. - Colin Conwell; Tomer D. Ullman (CoRR, 2022)

A sparse null code emerges in deep neural networks. - Brian S. Robinson; Nathan Drenkow; Colin Conwell; Michael F. Bonner (UniReps, 2023)

Revealing Vision-Language Integration in the Brain with Multimodal Networks. - Vighnesh Subramaniam; Colin Conwell; Christopher Wang; Gabriel Kreiman; Boris Katz; Ignacio Cases; Andrei Barbu (ICML, 2024)

Training the Untrainable: Introducing Inductive Bias via Representational Alignment. - Vighnesh Subramaniam; David Mayo; Colin Conwell; Tomaso A. Poggio; Boris Katz; Brian Cheung; Andrei Barbu (CoRR, 2024)

Using Multimodal Deep Neural Networks to Disentangle Language from Visual Aesthetics. - Colin Conwell; Christopher Hamblin; Chelsea Boccagno; David Mayo; Jesse Cummings; Leyla Isik; Andrei Barbu (CoRR, 2024)

Relations, Negations, and Numbers: Looking for Logic in Generative Text-to-Image Models. - Colin Conwell; Rupert Tawiah-Quashie; Tomer D. Ullman (CoRR, 2024)

Modeling dynamic social vision highlights gaps between deep learning and humans. - Kathy Garcia; Emalie McMahon; Colin Conwell; Michael F. Bonner; Leyla Isik (ICLR, 2025)