| Learning diverse and discriminative representations via the principle of maximal coding rate reduction Y Yu, KHR Chan, C You, C Song, Y Ma Advances in Neural Information Processing Systems 33, 9422-9434, 2020 | 162 | 2020 |
| Redunet: A white-box deep network from the principle of maximizing rate reduction KHR Chan, Y Yu, C You, H Qi, J Wright, Y Ma Journal of Machine Learning Research 23 (114), 1-103, 2022 | 101 | 2022 |
| CTRL: Closed-Loop Transcription to an LDR via Minimaxing Rate Reduction X Dai, S Tong, M Li, Z Wu, M Psenka, KHR Chan, P Zhai, Y Yu, X Yuan, ... Entropy 24 (4), 456, 2022 | 22 | 2022 |
| Deep Networks from the Principle of Rate Reduction KHR Chan, Y Yu, C You, H Qi, J Wright, Y Ma arXiv preprint arXiv:2010.14765, 2020 | 17 | 2020 |
| Closed-loop data transcription to an ldr via minimaxing rate reduction X Dai, S Tong, M Li, Z Wu, M Psenka, KHR Chan, P Zhai, Y Yu, X Yuan, ... arXiv preprint arXiv:2111.06636, 2021 | 10 | 2021 |
| Efficient Maximal Coding Rate Reduction by Variational Forms C Baek, Z Wu, KHR Chan, T Ding, Y Ma, BD Haeffele Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022 | 9 | 2022 |
| Variational Information Pursuit for Interpretable Predictions A Chattopadhyay, KHR Chan, BD Haeffele, D Geman, R Vidal arXiv preprint arXiv:2302.02876, 2023 | 8 | 2023 |
| Budget constrained machine learning for early prediction of adverse outcomes for COVID‑19 patients S Nguyen, KHR Chan, J Cadena, B Soper, P Kiszka, L Womack, M Work, ... Scientific Reports, 1112-1114, 2021 | 7 | 2021 |
| Unsupervised manifold linearizing and clustering T Ding, S Tong, KHR Chan, X Dai, Y Ma, BD Haeffele Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2023 | 6 | 2023 |
| COVID‐19 outcomes in patients with cancer: Findings from the University of California health system database DH Kwon, J Cadena, S Nguyen, KHR Chan, B Soper, AL Gryshuk, ... Cancer medicine 11 (11), 2204-2215, 2022 | 6 | 2022 |
| Dynamic modeling of hospitalized COVID-19 patients reveals disease state–dependent risk factors BC Soper, J Cadena, S Nguyen, KHR Chan, P Kiszka, L Womack, M Work, ... Journal of the American Medical Informatics Association 29 (5), 864-872, 2022 | 2 | 2022 |
| Subspace Locally Competitive Algorithms DM Paiton, S Shepard, KHR Chan, BA Olshausen Proceedings of the Neuro-inspired Computational Elements Workshop, 1-8, 2020 | 2 | 2020 |
| Knowledge Pursuit Prompting for Zero-Shot Multimodal Synthesis J Luo, KHR Chan, D Dimos, R Vidal arXiv preprint arXiv:2311.17898, 2023 | 1 | 2023 |
| End-to-End Framework for Imputation and State Discovery in Longitudinal Energy Data A Ladd, KHR Chan, S Nguyen, J Cadena, B Ng Proceedings of the Twelfth ACM International Conference on Future Energy …, 2021 | 1 | 2021 |
| Learning Interpretable Queries for Explainable Image Classification with Information Pursuit S Kolek, A Chattopadhyay, KHR Chan, H Andrade-Loarca, G Kutyniok, ... arXiv preprint arXiv:2312.11548, 2023 | | 2023 |
| Bootstrapping Variational Information Pursuit with Foundation Models for Interpretable Image Classification A Chattopadhyay, KHR Chan, R Vidal The Twelfth International Conference on Learning Representations, 2023 | | 2023 |
| Variational Information Pursuit with Large Language and Multimodal Models for Interpretable Predictions KHR Chan, A Chattopadhyay, BD Haeffele, R Vidal arXiv preprint arXiv:2308.12562, 2023 | | 2023 |
| Budget Constrained Machine Learning for Early Prediction of Adverse Outcomes for COVID-19 Patients JE Cadena Pico, BC Soper, P Ray, CP Mguyen, R Chan Lawrence Livermore National Lab.(LLNL), Livermore, CA (United States), 2021 | | 2021 |
| COVID-19 Outcomes in Patients with Cancer: Findings from the University of California Health System Database (preprint) DH Kwon, JEC Pico, S Nguyen, KHR Chan, B Soper, A Gryshuk, PH Ray, ... | | 2021 |
| EARLY PREDICTION OF ADVERSE OUTCOMES FOR COVID-19 PATIENTS UNDER COST CONSTRAINTS S Nguyen, KHR Chan, J Cadena, B Soper, P Kiszka, L Womack, M Work, ... Journal of Investigative Medicine, 1112-1114, 2021 | | 2021 |
Yi Ma (马毅)Professor of EECS, UC Berkeley; Director of IDS & Head of CS, University of Hong KongVerified email at eecs.berkeley.edu
