| 2025 | ICCV | Learning Interpretable Queries for Explainable Image Classification with Information Pursuit. | Stefan Kolek, Aditya Chattopadhyay, Kwan Ho Ryan Chan, Hctor Andrade-Loarca, Gitta Kutyniok, Ren Vidal |
| 2025 | ICLR | InCoDe: Interpretable Compressed Descriptions For Image Generation. | Armand Comas Massague, Aditya Chattopadhyay, Feliu Formosa, Changyu Liu, Octavia I. Camps, Ren Vidal |
| 2024 | ICLR | Bootstrapping Variational Information Pursuit with Large Language and Vision Models for Interpretable Image Classification. | Aditya Chattopadhyay, Kwan Ho Ryan Chan, Ren Vidal |
| 2024 | ICML | Performance Bounds for Active Binary Testing with Information Maximization. | Aditya Chattopadhyay, Benjamin David Haeffele, Ren Vidal, Donald Geman |
| 2023 | ICLR | Variational Information Pursuit for Interpretable Predictions. | Aditya Chattopadhyay, Kwan Ho Ryan Chan, Benjamin David Haeffele, Donald Geman, Ren Vidal |
| 2023 | WACV | Learning Graph Variational Autoencoders with Constraints and Structured Priors for Conditional Indoor 3D Scene Generation. | Aditya Chattopadhyay, Xi Zhang, David Paul Wipf, Himanshu Arora, Ren Vidal |
| 2019 | ICML | Neural Network Attributions: A Causal Perspective. | Aditya Chattopadhyay, Piyushi Manupriya, Anirban Sarkar, Vineeth N. Balasubramanian |
| 2018 | WACV | Grad-CAM++: Generalized Gradient-Based Visual Explanations for Deep Convolutional Networks. | Aditya Chattopadhyay, Anirban Sarkar, Prantik Howlader, Vineeth N. Balasubramanian |