Grad-CAM++: Generalized Gradient-Based Visual Explanations for Deep Convolutional Networks. - Aditya Chattopadhyay; Anirban Sarkar 001; Prantik Howlader; Vineeth N. Balasubramanian (WACV, 2018)

Neural Network Attributions: A Causal Perspective. - Aditya Chattopadhyay; Piyushi Manupriya; Anirban Sarkar 001; Vineeth N. Balasubramanian (ICML, 2019)

Structured Graph Variational Autoencoders for Indoor Furniture layout Generation. - Aditya Chattopadhyay; Xi Zhang; David Paul Wipf; Himanshu Arora; René Vidal (CoRR, 2022)

Variational Information Pursuit for Interpretable Predictions. - Aditya Chattopadhyay; Kwan Ho Ryan Chan; Benjamin David Haeffele; Donald Geman; René Vidal (ICLR, 2023)

Information Maximization Perspective of Orthogonal Matching Pursuit with Applications to Explainable AI. - Aditya Chattopadhyay; Ryan Pilgrim; René Vidal (NeurIPS, 2023)

Learning Graph Variational Autoencoders with Constraints and Structured Priors for Conditional Indoor 3D Scene Generation. - Aditya Chattopadhyay; Xi Zhang; David Paul Wipf; Himanshu Arora; René Vidal (WACV, 2023)

Variational Information Pursuit with Large Language and Multimodal Models for Interpretable Predictions. - Kwan Ho Ryan Chan; Aditya Chattopadhyay; Benjamin David Haeffele; René Vidal (CoRR, 2023)

Learning Interpretable Queries for Explainable Image Classification with Information Pursuit. - Stefan Kolek; Aditya Chattopadhyay; Kwan Ho Ryan Chan; Héctor Andrade-Loarca; Gitta Kutyniok; René Vidal (CoRR, 2023)

Interpretable by Design: Learning Predictors by Composing Interpretable Queries. - Aditya Chattopadhyay; Stewart Slocum; Benjamin D. Haeffele; René Vidal; Donald Geman (IEEE Trans. Pattern Anal. Mach. Intell., 2023)

Bootstrapping Variational Information Pursuit with Large Language and Vision Models for Interpretable Image Classification. - Aditya Chattopadhyay; Kwan Ho Ryan Chan; René Vidal (ICLR, 2024)

Performance Bounds for Active Binary Testing with Information Maximization. - Aditya Chattopadhyay; Benjamin David Haeffele; René Vidal; Donald Geman (ICML, 2024)

PaCE: Parsimonious Concept Engineering for Large Language Models. - Jinqi Luo; Tianjiao Ding; Kwan Ho Ryan Chan; Darshan Thaker; Aditya Chattopadhyay; Chris Callison-Burch; René Vidal (NeurIPS, 2024)

InCoDe: Interpretable Compressed Descriptions For Image Generation. - Armand Comas Massague; Aditya Chattopadhyay; Feliu Formosa; Changyu Liu; Octavia I. Camps; René Vidal (ICLR, 2025)