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A Unified, Scalable Framework for Neural Population Decoding

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

Accepted at NeurIPS 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

Accepted at NeurIPS 2023, Spotlight

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 Veli膷kovi膰, Eva L. Dyer

International Conference on Machine Learning (ICML), 2023

Transcriptomic cell type structures in vivo neuronal activity across multiple time scales

Aidan Schneider+, Mehdi Azabou+, Louis McDougall-Vigier, David Parks, Sahara Ensley, Kiran Bhaskaran-Nair, Tom Nowakowski, Eva L. Dyer*, Keith B. Hengen*

+Contributed equally as co-first authors

Cell Reports, Volume 42, Issue 4, April 2023.

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

Michael Mendelson+, Mehdi Azabou+, Suma Jacob, Nicola Grissom, David P. Barrow, Becket Ebitz, Alexander Herman, Eva L. Dyer

+Contributed equally as co-first authors

2023 11th International IEEE/EMBS Conference on Neural Engineering (NER), Baltimore, Maryland, April 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

2023 11th International IEEE/EMBS Conference on Neural Engineering (NER), Baltimore, Maryland, April 2023

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

Neural Information Processing Systems (NeurIPS), 2022

Large-scale representation learning on graphs via bootstrapping

Shantanu Thakoor, Corentin Tallec, Mohammad Gheshlaghi Azar, Mehdi Azabou, Eva L. Dyer, Remi Munos, Petar Veli膷kovi膰, Michal Valko

International Conference on Learning Representations (ICLR), 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, Chris Liding, Carolina Urzay, William Gray-Roncal, Erik Christopher Johnson, Eva L. Dyer

Neural Information Processing Systems (NeurIPS) Datasets and Benchmarks Track, 2022

Learning Behavior Representations Through Multi-Timescale Bootstrapping

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

Conference on Vision and Pattern Recognition (CVPR), Workshop on Multi-Agent Behavior (Oral), 2022

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

Neural Information Processing Systems (NeurIPS), accepted for Oral (1% submissions), 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, Bernardo Avila-Pires, Lindsey Kitchell, Keith B. Hengen, William Gray-Roncal, Michal Valko, Eva L. Dyer

Neural Information Processing Systems (NeurIPS), Workshop on Self-supervised Learning: Theory and Practice (Oral), Feb 2021

Using self-supervision and augmentations to build insights into neural coding

Mehdi Azabou+, Max Dabagia+, Ran Liu+, Chi-Heng Lin, Keith B. Hengen, Eva L. Dyer

+Contributed equally as co-first authors

Neural Information Processing Systems (NeurIPS), Workshop on Self-supervised Learning: Theory and Practice, Feb 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

International Conference on Machine Learning (ICML), 2021

Abstracts

Detecting change points in neural population activity with contrastive metric learning

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

Conference on Cognitive Computational Neuroscience (CCN), 2022