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2020 – today
- 2023
[c2]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: 1-4- 2022
- [j1]David F. Parks
, Kateryna Voitiuk, Jinghui Geng, Matthew A. T. Elliott, Matthew G. Keefe, Erik A. Jung, Ash Robbins, Pierre V. Baudin, Victoria T. Ly, Nico Hawthorne, Dylan Yong, Sebastian E. Sanso, Nick Rezaee, Jess L. Sevetson, Spencer T. Seiler, Robert Currie, Alex A. Pollen, Keith B. Hengen, Tomasz J. Nowakowski, Mohammed Andres Mostajo-Radji, Sofie R. Salama, Mircea Teodorescu, David Haussler:
IoT cloud laboratory: Internet of Things architecture for cellular biology. Internet Things 20: 100618 (2022) - [i3]Nauman Ahad, Eva L. Dyer, Keith B. Hengen, Yao Xie, Mark A. Davenport:
Learning Sinkhorn divergences for supervised change point detection. CoRR abs/2202.04000 (2022) - 2021
- [c1]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: 10587-10599 - [i2]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 abs/2102.10106 (2021) - [i1]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 abs/2111.02338 (2021)
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