Demystifying excessively volatile human learning: A Bayesian persistent prior and a neural approximation. - Chaitanya Ryali; Gautam Reddy; Angela J. Yu (NeurIPS, 2018)

Beauty-in-averageness and its contextual modulations: A Bayesian statistical account. - Chaitanya Ryali; Angela J. Yu (NeurIPS, 2018)

A Model-Based Investigating of the Biological Origin of Human Social Perception of Faces. - Jingya Huang; Jianling Liu; Dalin Guo; Chaitanya Ryali; Jinyan Guan; Angela J. Yu (CogSci, 2019)

Leveraging Computer Vision Face Representation to Understand Human Face Representation. - Chaitanya Ryali; Xiaotian Wang; Angela J. Yu (CogSci, 2020)

Leveraging Computer Vision Face Representation to Understand Human Face Representation. - Chaitanya Ryali (2021)

Hiera: A Hierarchical Vision Transformer without the Bells-and-Whistles. - Chaitanya Ryali; Yuan-Ting Hu; Daniel Bolya; Chen Wei 005; Haoqi Fan 001; Po-Yao Huang 001; Vaibhav Aggarwal; Arkabandhu Chowdhury; Omid Poursaeed; Judy Hoffman; Jitendra Malik; Yanghao Li; et al. (ICML, 2023)

MAViL: Masked Audio-Video Learners. - Po-Yao Huang 001; Vasu Sharma; Hu Xu 001; Chaitanya Ryali; Haoqi Fan 001; Yanghao Li; Shang-Wen Li 001; Gargi Ghosh; Jitendra Malik; Christoph Feichtenhofer (NeurIPS, 2023)

Window Attention is Bugged: How not to Interpolate Position Embeddings. - Daniel Bolya; Chaitanya Ryali; Judy Hoffman; Christoph Feichtenhofer (ICLR, 2024)

SAM 2: Segment Anything in Images and Videos. - Nikhila Ravi; Valentin Gabeur; Yuan-Ting Hu; Ronghang Hu; Chaitanya Ryali; Tengyu Ma 005; Haitham Khedr; Roman Rädle; Chloé Rolland; Laura Gustafson; Eric Mintun; Junting Pan; et al. (ICLR, 2025)