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Kwan Ho Ryan Chan
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Journal Articles
- 2022
- [j3]Xili Dai, Shengbang Tong, Mingyang Li, Ziyang Wu, Michael Psenka, Kwan Ho Ryan Chan, Pengyuan Zhai, Yaodong Yu
, Xiaojun Yuan, Heung-Yeung Shum
, Yi Ma:
CTRL: Closed-Loop Transcription to an LDR via Minimaxing Rate Reduction. Entropy 24(4): 456 (2022) - [j2]Braden C. Soper, Jose Cadena
, Sam Nguyen, Kwan Ho Ryan Chan, Paul Kiszka, Lucas Aaron Womack, Mark Work, Joan M. Duggan, Steven T. Haller, Jennifer A. Hanrahan
, David J. Kennedy, Deepa Mukundan, Priyadip Ray:
Dynamic modeling of hospitalized COVID-19 patients reveals disease state-dependent risk factors. J. Am. Medical Informatics Assoc. 29(5): 864-872 (2022) - [j1]Kwan Ho Ryan Chan, Yaodong Yu, Chong You, Haozhi Qi, John Wright, Yi Ma:
ReduNet: A White-box Deep Network from the Principle of Maximizing Rate Reduction. J. Mach. Learn. Res. 23: 114:1-114:103 (2022)
Conference and Workshop Papers
- 2024
- [c7]Aditya Chattopadhyay, Kwan Ho Ryan Chan, René Vidal:
Bootstrapping Variational Information Pursuit with Large Language and Vision Models for Interpretable Image Classification. ICLR 2024 - 2023
- [c6]Tianjiao Ding, Shengbang Tong, Kwan Ho Ryan Chan, Xili Dai, Yi Ma, Benjamin D. Haeffele:
Unsupervised Manifold Linearizing and Clustering. ICCV 2023: 5427-5438 - [c5]Aditya Chattopadhyay, Kwan Ho Ryan Chan, Benjamin David Haeffele, Donald Geman, René Vidal:
Variational Information Pursuit for Interpretable Predictions. ICLR 2023 - 2022
- [c4]Christina Baek, Ziyang Wu, Kwan Ho Ryan Chan, Tianjiao Ding, Yi Ma, Benjamin D. Haeffele:
Efficient Maximal Coding Rate Reduction by Variational Forms. CVPR 2022: 490-498 - 2021
- [c3]Alexander Ladd, Kwan Ho Ryan Chan, Sam Nguyen, Jose Cadena, Brenda Ng:
End-to-End Framework for Imputation and State Discovery in Longitudinal Energy Data. e-Energy 2021: 475-482 - 2020
- [c2]Dylan M. Paiton, Steven Shepard, Kwan Ho Ryan Chan, Bruno A. Olshausen:
Subspace Locally Competitive Algorithms. NICE 2020: 9:1-9:8 - [c1]Yaodong Yu, Kwan Ho Ryan Chan, Chong You, Chaobing Song, Yi Ma:
Learning Diverse and Discriminative Representations via the Principle of Maximal Coding Rate Reduction. NeurIPS 2020
Informal and Other Publications
- 2024
- [i11]Jinqi Luo, Tianjiao Ding, Kwan Ho Ryan Chan, Darshan Thaker, Aditya Chattopadhyay, Chris Callison-Burch, René Vidal:
PaCE: Parsimonious Concept Engineering for Large Language Models. CoRR abs/2406.04331 (2024) - 2023
- [i10]Tianjiao Ding, Shengbang Tong, Kwan Ho Ryan Chan, Xili Dai, Yi Ma, Benjamin D. Haeffele:
Unsupervised Manifold Linearizing and Clustering. CoRR abs/2301.01805 (2023) - [i9]Aditya Chattopadhyay, Kwan Ho Ryan Chan, Benjamin D. Haeffele, Donald Geman, René Vidal:
Variational Information Pursuit for Interpretable Predictions. CoRR abs/2302.02876 (2023) - [i8]Kwan Ho Ryan Chan, Aditya Chattopadhyay, Benjamin David Haeffele, René Vidal:
Variational Information Pursuit with Large Language and Multimodal Models for Interpretable Predictions. CoRR abs/2308.12562 (2023) - [i7]Jinqi Luo, Kwan Ho Ryan Chan, Dimitris Dimos, René Vidal:
Knowledge Pursuit Prompting for Zero-Shot Multimodal Synthesis. CoRR abs/2311.17898 (2023) - [i6]Stefan Kolek, Aditya Chattopadhyay, Kwan Ho Ryan Chan, Héctor Andrade-Loarca, Gitta Kutyniok, René Vidal:
Learning Interpretable Queries for Explainable Image Classification with Information Pursuit. CoRR abs/2312.11548 (2023) - 2022
- [i5]Christina Baek, Ziyang Wu, Kwan Ho Ryan Chan, Tianjiao Ding, Yi Ma, Benjamin D. Haeffele:
Efficient Maximal Coding Rate Reduction by Variational Forms. CoRR abs/2204.00077 (2022) - 2021
- [i4]Kwan Ho Ryan Chan, Yaodong Yu, Chong You, Haozhi Qi, John Wright, Yi Ma:
ReduNet: A White-box Deep Network from the Principle of Maximizing Rate Reduction. CoRR abs/2105.10446 (2021) - [i3]Xili Dai, Shengbang Tong, Mingyang Li, Ziyang Wu, Kwan Ho Ryan Chan, Pengyuan Zhai, Yaodong Yu, Michael Psenka, Xiaojun Yuan, Heung-Yeung Shum, Yi Ma:
Closed-Loop Data Transcription to an LDR via Minimaxing Rate Reduction. CoRR abs/2111.06636 (2021) - 2020
- [i2]Yaodong Yu, Kwan Ho Ryan Chan, Chong You, Chaobing Song, Yi Ma:
Learning Diverse and Discriminative Representations via the Principle of Maximal Coding Rate Reduction. CoRR abs/2006.08558 (2020) - [i1]Kwan Ho Ryan Chan, Yaodong Yu, Chong You, Haozhi Qi, John Wright, Yi Ma:
Deep Networks from the Principle of Rate Reduction. CoRR abs/2010.14765 (2020)
Coauthor Index
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