Mehdi Azabou

Publication Activity (10 Years)

Years Active: 2020-2024
Publications (10 Years): 22

Top Topics

Neural Dynamics

Levels Of Abstraction

Message Passing

Behavior Analysis

Top Venues

Publications

Yizi Zhang, Yanchen Wang, Donato Jimenez-Beneto, Zixuan Wang, Mehdi Azabou, Blake A. Richards, Olivier Winter, International Brain Laboratory, Eva L. Dyer, Liam Paninski, Cole L. Hurwitz
Towards a "universal translator" for neural dynamics at single-cell, single-spike resolution. CoRR (2024)
Divyansha Lachi, Mehdi Azabou, Vinam Arora, Eva L. Dyer
GraphFM: A Scalable Framework for Multi-Graph Pretraining. CoRR (2024)
Mehdi Azabou, Michael Mendelson, Nauman Ahad, Maks Sorokin, Shantanu Thakoor, Carolina Urzay, Eva L. Dyer
Relax, it doesn't matter how you get there: A new self-supervised approach for multi-timescale behavior analysis. NeurIPS (2023)
Michael J. Mendelson, Mehdi Azabou, Suma Jacob, Nicola Grissom, David Darrow, Becket Ebitz, Alexander Herman, Eva L. Dyer
Learning signatures of decision making from many individuals playing the same game. CoRR (2023)
Mehdi Azabou, Michael Mendelson, Nauman Ahad, Maks Sorokin, Shantanu Thakoor, Carolina Urzay, Eva L. Dyer
Relax, it doesn't matter how you get there: A new self-supervised approach for multi-timescale behavior analysis. CoRR (2023)
Mehdi Azabou, Vinam Arora, Venkataramana Ganesh, Ximeng Mao, Santosh Nachimuthu, Michael Mendelson, Blake A. Richards, Matthew G. Perich, Guillaume Lajoie, Eva L. Dyer
A Unified, Scalable Framework for Neural Population Decoding. NeurIPS (2023)
Mehdi Azabou, Venkataramana Ganesh, Shantanu Thakoor, Chi-Heng Lin, Lakshmi Sathidevi, Ran Liu, Michal Valko, Petar Velickovic, Eva L. Dyer
Half-Hop: A graph upsampling approach for slowing down message passing. CoRR (2023)
Carolina Urzay, Nauman Ahad, Mehdi Azabou, Aidan Schneider, Geethika Atamkuri, Keith B. Hengen, Eva L. Dyer
Detecting change points in neural population activity with contrastive metric learning. NER (2023)
Michael J. Mendelson, Mehdi Azabou, Suma Jacob, Nicola Grissom, David Darrow, Becket Ebitz, Alexander Herman, Eva L. Dyer
Learning signatures of decision making from many individuals playing the same game. NER (2023)
Mehdi Azabou, Venkataramana Ganesh, Shantanu Thakoor, Chi-Heng Lin, Lakshmi Sathidevi, Ran Liu, Michal Valko, Petar Velickovic, Eva L. Dyer
Half-Hop: A graph upsampling approach for slowing down message passing. ICML (2023)
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
MTNeuro: A Benchmark for Evaluating Representations of Brain Structure Across Multiple Levels of Abstraction. CoRR (2023)
Mehdi Azabou, Vinam Arora, Venkataramana Ganesh, Ximeng Mao, Santosh Nachimuthu, Michael J. Mendelson, Blake A. Richards, Matthew G. Perich, Guillaume Lajoie, Eva L. Dyer
A Unified, Scalable Framework for Neural Population Decoding. CoRR (2023)
Ran Liu, Mehdi Azabou, Max Dabagia, Jingyun Xiao, Eva L. Dyer
Seeing the forest and the tree: Building representations of both individual and collective dynamics with transformers. NeurIPS (2022)
Ran Liu, Mehdi Azabou, Max Dabagia, Jingyun Xiao, Eva L. Dyer
Seeing the forest and the tree: Building representations of both individual and collective dynamics with transformers. CoRR (2022)
Mehdi Azabou, Michael Mendelson, Maks Sorokin, Shantanu Thakoor, Nauman Ahad, Carolina Urzay, Eva L. Dyer
Learning Behavior Representations Through Multi-Timescale Bootstrapping. CoRR (2022)
Jorge Quesada, Lakshmi Sathidevi, Ran Liu, Nauman Ahad, Joy M. Jackson, Mehdi Azabou, Jingyun Xiao, Christopher Liding, Matthew Jin, Carolina Urzay, William Gray-Roncal, Erik Johnson, Eva L. Dyer
MTNeuro: A Benchmark for Evaluating Representations of Brain Structure Across Multiple Levels of Abstraction. NeurIPS (2022)
Shantanu Thakoor, Corentin Tallec, Mohammad Gheshlaghi Azar, Mehdi Azabou, Eva L. Dyer, Rémi Munos, Petar Velickovic, Michal Valko
Large-Scale Representation Learning on Graphs via Bootstrapping. ICLR (2022)
Ran Liu, Mehdi Azabou, Max Dabagia, Chi-Heng Lin, Mohammad Gheshlaghi Azar, Keith B. Hengen, Michal Valko, Eva L. Dyer
Drop, Swap, and Generate: A Self-Supervised Approach for Generating Neural Activity. CoRR (2021)
Chi-Heng Lin, Mehdi Azabou, Eva L. Dyer
Making transport more robust and interpretable by moving data through a small number of anchor points. ICML (2021)
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
Mine Your Own vieW: Self-Supervised Learning Through Across-Sample Prediction. CoRR (2021)
Ran Liu, Mehdi Azabou, Max Dabagia, Chi-Heng Lin, Mohammad Gheshlaghi Azar, Keith B. Hengen, Michal Valko, Eva L. Dyer
Drop, Swap, and Generate: A Self-Supervised Approach for Generating Neural Activity. NeurIPS (2021)
Chi-Heng Lin, Mehdi Azabou, Eva L. Dyer
Making transport more robust and interpretable by moving data through a small number of anchor points. CoRR (2020)