Resources for the paper titled "Evaluating Latent Space Robustness and Uncertainty of EEG-ML Models under Realistic Distribution Shifts". Accepted at NeurIPS 2022.
NeurIPS 2022 page - https://neurips.cc/virtual/2022/poster/52788
Slides & poster - https://drive.google.com/drive/folders/10TOWbpDmL0B2xHiznV6D02oka1h4hVQs?usp=sharing
ArXiv preprint - https://arxiv.org/abs/2209.11233
OpenReview - https://openreview.net/forum?id=KRk0lBRPpOC
Code for reproducing results - https://figshare.com/s/2a8eb98b47f050b99b16
Code for evaluating your own models using your own data - coming soon!
NMT dataset links:
- (original) https://dll.seecs.nust.edu.pk/downloads/
- (re-uploaded) https://drive.google.com/file/d/1jD_AcmfoaIfkOiO5lSU4J6IxHZtalnTk/view
Contact:
- Neeraj - nwagh2@illinois.edu
- Yoga (PI) - varatha2@illinois.edu
Citation:
Wagh, N., Wei, J., Rawal, S., Berry, B., & Varatharajah, Y. Evaluating Latent Space Robustness and Uncertainty of EEG-ML Models under Realistic Distribution Shifts.