Mehdi Azabou
Georgia Institute of Technology
H-index: 6
North America-United States
Top articles of Mehdi Azabou
A Unified, Scalable Framework for Neural Population Decoding
Advances in Neural Information Processing Systems
2024/2/13
Half-Hop: A graph upsampling approach for slowing down message passing
2023/7/3
Mehdi Azabou
H-Index: 1
Ran Liu
H-Index: 15
Transcriptomic cell type structures in vivo neuronal activity across multiple timescales
Cell reports
2023/4/25
Detecting change points in neural population activity with contrastive metric learning
2023/4/24
Mehdi Azabou
H-Index: 1
Aidan Schneider
H-Index: 3
Learning signatures of decision making from many individuals playing the same game
2023/4/24
Relax, it doesn't matter how you get there: A new self-supervised approach for multi-timescale behavior analysis
NeurIPS 2023, Spotlight
2023/3/15
Mehdi Azabou
H-Index: 1
Maks Sorokin
H-Index: 0
Learning behavior representations through multi-timescale bootstrapping
arXiv preprint arXiv:2206.07041
2022/6/14
Mehdi Azabou
H-Index: 1
Maks Sorokin
H-Index: 0
Seeing the forest and the tree: Building representations of both individual and collective dynamics with transformers
Advances in neural information processing systems
2022/12/6
Large-scale representation learning on graphs via bootstrapping
International Conference on Learning Representations (ICLR)
2022
Mehdi Azabou
H-Index: 1
MTNeuro: A Benchmark for Evaluating Representations of Brain Structure Across Multiple Levels of Abstraction
Advances in neural information processing systems
2022/12/6
Drop, swap, and generate: A self-supervised approach for generating neural activity
Advances in Neural Information Processing Systems
2021/11
Making transport more robust and interpretable by moving data through a small number of anchor points
International Conference on Machine Learning (ICML)
2021/7
Mehdi Azabou
H-Index: 1
Mine your own view: Self-supervised learning through across-sample prediction
arXiv preprint arXiv:2102.10106
2021/2/19
Using self-supervision and augmentations to build insights into neural coding
Proceedings of Workshop on Self-Supervised Learning-Theory and Practice on NeurIPS, Proceedings of Machine Learning Research
2021
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