Mehdi Azabou - RankMe

30 papers A* 11Journal 17Unranked 2

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	Decoding Dynamic Visual Experience from Calcium Imaging via Cell-Pattern-Aware SSL. CoRR Sangyoon Bae, Mehdi Azabou, Jiook Cha, Blake A. Richards
2025	J	`jnl`	Generalizable, real-time neural decoding with hybrid state-space models. CoRR Avery Hee-Woon Ryoo, Nanda H. Krishna, Ximeng Mao, Mehdi Azabou, Eva L. Dyer, Matthew G. Perich, Guillaume Lajoie
2025	J	`jnl`	GraphFM: A generalist graph transformer that learns transferable representations across diverse domains. Trans. Mach. Learn. Res. Divyansha Lachi, Mehdi Azabou, Vinam Arora, Eva L. Dyer
2025	J	`jnl`	Know Thyself by Knowing Others: Learning Neuron Identity from Population Context. CoRR Vinam Arora, Divyansha Lachi, Ian Jarratt Knight, Mehdi Azabou, Blake A. Richards, Cole L. Hurwitz, Joshua H. Siegle, Eva L. Dyer
2025	A*	`conf`	Multi-session, multi-task neural decoding from distinct cell-types and brain regions. ICLR Mehdi Azabou, Krystal Xuejing Pan, Vinam Arora, Ian Jarratt Knight, Eva L. Dyer, Blake Aaron Richards
2025	A*	`conf`	Neural Encoding and Decoding at Scale. ICML Yizi Zhang, Yanchen Wang, Mehdi Azabou, Alexandre Andre, Zixuan Wang, Hanrui Lyu, International Brain Laboratory, Eva L. Dyer, Liam Paninski, Cole Lincoln Hurwitz
2025	J	`jnl`	Neural Encoding and Decoding at Scale. CoRR Yizi Zhang, Yanchen Wang, Mehdi Azabou, Alexandre Andre, Zixuan Wang, Hanrui Lyu, International Brain Laboratory, Eva L. Dyer, Liam Paninski, Cole L. Hurwitz
2024	J	`jnl`	GraphFM: A Scalable Framework for Multi-Graph Pretraining. CoRR Divyansha Lachi, Mehdi Azabou, Vinam Arora, Eva L. Dyer
2024	A*	`conf`	Towards a "Universal Translator" for Neural Dynamics at Single-Cell, Single-Spike Resolution. NeurIPS Yizi Zhang, Yanchen Wang, Donato Jiménez-Benetó, Zixuan Wang, Mehdi Azabou, Blake A. Richards, Renee Tung, Olivier Winter, International Brain Laboratory, Eva L. Dyer, Liam Paninski, Cole L. Hurwitz
2024	J	`jnl`	Towards a "universal translator" for neural dynamics at single-cell, single-spike resolution. CoRR Yizi Zhang, Yanchen Wang, Donato Jiménez-Benetó, Zixuan Wang, Mehdi Azabou, Blake A. Richards, Olivier Winter, International Brain Laboratory, Eva L. Dyer, Liam Paninski, Cole L. Hurwitz
2023	A*	`conf`	A Unified, Scalable Framework for Neural Population Decoding. NeurIPS Mehdi Azabou, Vinam Arora, Venkataramana Ganesh, Ximeng Mao, Santosh Nachimuthu, Michael Mendelson, Blake A. Richards, Matthew G. Perich, Guillaume Lajoie, Eva L. Dyer
2023	J	`jnl`	A Unified, Scalable Framework for Neural Population Decoding. CoRR Mehdi Azabou, Vinam Arora, Venkataramana Ganesh, Ximeng Mao, Santosh Nachimuthu, Michael J. Mendelson, Blake A. Richards, Matthew G. Perich, Guillaume Lajoie, Eva L. Dyer
2023	—	`conf`	Detecting change points in neural population activity with contrastive metric learning. NER Carolina Urzay, Nauman Ahad, Mehdi Azabou, Aidan Schneider, Geethika Atamkuri, Keith B. Hengen, Eva L. Dyer
2023	A*	`conf`	Half-Hop: A graph upsampling approach for slowing down message passing. ICML Mehdi Azabou, Venkataramana Ganesh, Shantanu Thakoor, Chi-Heng Lin, Lakshmi Sathidevi, Ran Liu, Michal Valko, Petar Velickovic, Eva L. Dyer
2023	J	`jnl`	Half-Hop: A graph upsampling approach for slowing down message passing. CoRR Mehdi Azabou, Venkataramana Ganesh, Shantanu Thakoor, Chi-Heng Lin, Lakshmi Sathidevi, Ran Liu, Michal Valko, Petar Velickovic, Eva L. Dyer
2023	—	`conf`	Learning signatures of decision making from many individuals playing the same game. NER Michael J. Mendelson, Mehdi Azabou, Suma Jacob, Nicola Grissom, David Darrow, Becket Ebitz, Alexander Herman, Eva L. Dyer
2023	J	`jnl`	Learning signatures of decision making from many individuals playing the same game. CoRR Michael J. Mendelson, Mehdi Azabou, Suma Jacob, Nicola Grissom, David Darrow, Becket Ebitz, Alexander Herman, Eva L. Dyer
2023	J	`jnl`	MTNeuro: A Benchmark for Evaluating Representations of Brain Structure Across Multiple Levels of Abstraction. CoRR 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
2023	A*	`conf`	Relax, it doesn't matter how you get there: A new self-supervised approach for multi-timescale behavior analysis. NeurIPS Mehdi Azabou, Michael Mendelson, Nauman Ahad, Maks Sorokin, Shantanu Thakoor, Carolina Urzay, Eva L. Dyer
2023	J	`jnl`	Relax, it doesn't matter how you get there: A new self-supervised approach for multi-timescale behavior analysis. CoRR Mehdi Azabou, Michael Mendelson, Nauman Ahad, Maks Sorokin, Shantanu Thakoor, Carolina Urzay, Eva L. Dyer
2022	A*	`conf`	Large-Scale Representation Learning on Graphs via Bootstrapping. ICLR Shantanu Thakoor, Corentin Tallec, Mohammad Gheshlaghi Azar, Mehdi Azabou, Eva L. Dyer, Rémi Munos, Petar Velickovic, Michal Valko
2022	J	`jnl`	Learning Behavior Representations Through Multi-Timescale Bootstrapping. CoRR Mehdi Azabou, Michael Mendelson, Maks Sorokin, Shantanu Thakoor, Nauman Ahad, Carolina Urzay, Eva L. Dyer
2022	A*	`conf`	MTNeuro: A Benchmark for Evaluating Representations of Brain Structure Across Multiple Levels of Abstraction. NeurIPS 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
2022	A*	`conf`	Seeing the forest and the tree: Building representations of both individual and collective dynamics with transformers. NeurIPS Ran Liu, Mehdi Azabou, Max Dabagia, Jingyun Xiao, Eva L. Dyer
2022	J	`jnl`	Seeing the forest and the tree: Building representations of both individual and collective dynamics with transformers. CoRR Ran Liu, Mehdi Azabou, Max Dabagia, Jingyun Xiao, Eva L. Dyer
2021	A*	`conf`	Drop, Swap, and Generate: A Self-Supervised Approach for Generating Neural Activity. NeurIPS Ran Liu, Mehdi Azabou, Max Dabagia, Chi-Heng Lin, Mohammad Gheshlaghi Azar, Keith B. Hengen, Michal Valko, Eva L. Dyer
2021	J	`jnl`	Drop, Swap, and Generate: A Self-Supervised Approach for Generating Neural Activity. CoRR Ran Liu, Mehdi Azabou, Max Dabagia, Chi-Heng Lin, Mohammad Gheshlaghi Azar, Keith B. Hengen, Michal Valko, Eva L. Dyer
2021	A*	`conf`	Making transport more robust and interpretable by moving data through a small number of anchor points. ICML Chi-Heng Lin, Mehdi Azabou, Eva L. Dyer
2021	J	`jnl`	Mine Your Own vieW: Self-Supervised Learning Through Across-Sample Prediction. CoRR 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
2020	J	`jnl`	Making transport more robust and interpretable by moving data through a small number of anchor points. CoRR Chi-Heng Lin, Mehdi Azabou, Eva L. Dyer