Mehdi Azabou

According to our database, Mehdi Azabou authored at least 12 papers between 2021 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2023

Relax, it doesn't matter how you get there: A new self-supervised approach for multi-timescale behavior analysis.

Mehdi Azabou, Michael Mendelson, Nauman Ahad, Maks Sorokin, Shantanu Thakoor, Carolina Urzay, Eva L. Dyer

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

A Unified, Scalable Framework for Neural Population Decoding.

Mehdi Azabou, Vinam Arora, Venkataramana Ganesh, Ximeng Mao, Santosh Nachimuthu, Michael Mendelson, Blake A. Richards, Matthew G. Perich, Guillaume Lajoie, Eva L. Dyer

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Detecting change points in neural population activity with contrastive metric learning.

Carolina Urzay, Nauman Ahad, Mehdi Azabou, Aidan Schneider, Geethika Atamkuri, Keith B. Hengen, Eva L. Dyer

Proceedings of the 11th International IEEE/EMBS Conference on Neural Engineering, 2023

Learning signatures of decision making from many individuals playing the same game.

Michael J. Mendelson, Mehdi Azabou, Suma Jacob, Nicola Grissom, David Darrow, Becket Ebitz, Alexander Herman, Eva L. Dyer

Proceedings of the 11th International IEEE/EMBS Conference on Neural Engineering, 2023

Half-Hop: A graph upsampling approach for slowing down message passing.

Mehdi Azabou, Venkataramana Ganesh, Shantanu Thakoor, Chi-Heng Lin, Lakshmi Sathidevi, Ran Liu, Michal Valko, Petar Velickovic, Eva L. Dyer

Proceedings of the International Conference on Machine Learning, 2023

2022

Learning Behavior Representations Through Multi-Timescale Bootstrapping.

Mehdi Azabou, Michael Mendelson, Maks Sorokin, Shantanu Thakoor, Nauman Ahad, Carolina Urzay, Eva L. Dyer

CoRR, 2022

MTNeuro: A Benchmark for Evaluating Representations of Brain Structure Across Multiple Levels of Abstraction.

Jorge Quesada, Lakshmi Sathidevi, Ran Liu, Nauman Ahad, Joy M. Jackson, Mehdi Azabou, Jingyun Xiao, Christopher Liding, Matthew Jin, Carolina Urzay, William R. Gray Roncal, Erik C. Johnson, Eva L. Dyer

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Seeing the forest and the tree: Building representations of both individual and collective dynamics with transformers.

Ran Liu, Mehdi Azabou, Max Dabagia, Jingyun Xiao, Eva L. Dyer

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Large-Scale Representation Learning on Graphs via Bootstrapping.

Shantanu Thakoor, Corentin Tallec, Mohammad Gheshlaghi Azar, Mehdi Azabou, Eva L. Dyer, Rémi Munos, Petar Velickovic, Michal Valko

Proceedings of the Tenth International Conference on Learning Representations, 2022

2021

Mine Your Own vieW: Self-Supervised Learning Through Across-Sample Prediction.

Mehdi Azabou, Mohammad Gheshlaghi Azar, Ran Liu, Chi-Heng Lin, Erik C. Johnson, Kiran Bhaskaran-Nair, Max Dabagia, Keith B. Hengen, William R. Gray Roncal, Michal Valko, Eva L. Dyer

CoRR, 2021

Drop, Swap, and Generate: A Self-Supervised Approach for Generating Neural Activity.

Ran Liu, Mehdi Azabou, Max Dabagia, Chi-Heng Lin, Mohammad Gheshlaghi Azar, Keith B. Hengen, Michal Valko, Eva L. Dyer

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Making transport more robust and interpretable by moving data through a small number of anchor points.

Chi-Heng Lin, Mehdi Azabou, Eva L. Dyer

Proceedings of the 38th International Conference on Machine Learning, 2021