Thomas Serre

Associate Scientist

Thomas Serre is a Professor of Cognitive Linguistic & Psychological Sciences and Computer Science at Brown University. He received a Ph.D. in Neuroscience from MIT in 2006 and an MSc in EECS from Télécom Bretagne (France) in 2000. His research seeks to understand the neural computations supporting visual perception and it has been featured on the BBC and other news articles (The Economist, New Scientist, Scientific American, Technology Review, Slashdot, etc). He also holds an International Chair in AI within the Artificial and Natural Intelligence Toulouse Institute (France). Dr. Serre has been serving as an area chair and a senior program committee member for top-tier machine learning and computer vision conferences including AAAI, CVPR, ICML, ICLR, and NeurIPS. He also serves as an editor for the journals eLife and PLOS computational biology. He was the recipient of an NSF Early Career Award and DARPA’s Young Faculty Award and Director’s Award. Together with his team, he was awarded the 2021 PAMI Helmholtz Prize and the 2022 PAMI Mark Everingham Prize for their work on human action recognition.

Publications in association with ELLIS Alicante

2024

11/06

Colin, J., Goetschalckx, L., Fel, T., Boutin, V., Gopal, J., Serre, T, & Oliver, N. (2024). Local vs distributed representations: What is the right basis for interpretability?. arXiv:2411.03993.

2023

12/15

Fel, T., Boissin, T., Boutin, V., Picard, A., Novello, P., Colin, J., Linsley, D., Rousseau, T., Cadène, R., Gardes, L., & Serre, T. (2023). Unlocking Feature Visualization for Deeper Networks with MAgnitude Constrained Optimization. 37th Conference on Neural Information Processing Systems (NeurIPS), 36, 37813-37826.

07/03

Boutin, V., Fel, T., Singhal, L., Mukherji, R., Nagaraj, A., Colin, J., & Serre, T. (2023). Diffusion Models as Artists: Are we Closing the Gap between Humans and Machines?. Proceedings of the International Conference on Machine Learning (ICML), 2953-3002.

06/20

Fel, T., Picard, A., Bethune, L., Boissin, T., Vigouroux, D., Colin, J., Cadène, R., & Serre, T. (2023). CRAFT: Concept Recursive Activation FacTorization for Explainability. Conference on Computer Vision and Pattern Recognition (CVPR), 2711-2721.

2022

11/29

Zerroug, A., Vaishnav, M., Colin, J., Musslick, S., & Serre, T. (2022). A Benchmark for Compositional Visual Reasoning. 36th Conference on Neural Information Processing Systems (NeurIPS), Datasets and Benchmarks, 35, 29776-29788.

11/29

Colin, J., Fel, T., Cadène, R., & Serre, T. (2022). What I Cannot Predict, I Do Not Understand: A Human-Centered Evaluation Framework for Explainability Methods. 36th Conference on Neural Information Processing Systems (NeurIPS).

06/09

Fel, T., Hervier, L., Vigouroux, D., Poche, A., Plakoo, J., Cadène, R., Chalvidal, M., Colin, J., Boissin, T., Bethune, L., Picard, A., Nicodeme, C., Gardes, L., Flandin, G., & Serre, T. (2022). Xplique: A Deep Learning Explainability Toolbox. Conference on Computer Vision and Pattern Recognition (CVPR), Workshop on Explainable Artificial Intelligence for Computer Vision (XAI4CV).