Keith B. Hengen

According to our database, Keith B. Hengen authored at least 6 papers between 2021 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2025

Learning Sinkhorn Divergences for Change Point Detection.

Nauman Ahad, Eva L. Dyer, Keith B. Hengen, Yao Xie, Mark A. Davenport

IEEE Trans. Signal Process., 2025

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

Proceedings of the 11th International IEEE/EMBS Conference on Neural Engineering, 2023

2022

IoT cloud laboratory: Internet of Things architecture for cellular biology.

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

Internet Things, 2022

Learning Sinkhorn divergences for supervised change point detection.

Nauman Ahad, Eva L. Dyer, Keith B. Hengen, Yao Xie, Mark A. Davenport

CoRR, 2022

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, Keith B. Hengen, William R. Gray Roncal, Michal Valko, Eva L. Dyer

CoRR, 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

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021