Aditya Chattopadhyay

22 papers A* 7A 2Journal 13

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Learning When to Attend: Conditional Memory Access for Long-Context LLMs. CoRR Sakshi Choudhary, Aditya Chattopadhyay, Luca Zancato, Elvis Nunez, Matthew Trager, Wei Xia, Stefano Soatto
2025	J	`jnl`	Experience-Guided Adaptation of Inference-Time Reasoning Strategies. CoRR Adam Stein, Matthew Trager, Benjamin Bowman, Michael Kleinman, Aditya Chattopadhyay, Wei Xia, Stefano Soatto
2025	J	`jnl`	Gated KalmaNet: A Fading Memory Layer Through Test-Time Ridge Regression. CoRR Liangzu Peng, Aditya Chattopadhyay, Luca Zancato, Elvis Nunez, Wei Xia, Stefano Soatto
2025	A*	`conf`	InCoDe: Interpretable Compressed Descriptions For Image Generation. ICLR Armand Comas Massague, Aditya Chattopadhyay, Feliu Formosa, Changyu Liu, Octavia I. Camps, René Vidal
2025	J	`jnl`	LATTS: Locally Adaptive Test-Time Scaling. CoRR Theo Uscidda, Matthew Trager, Michael Kleinman, Aditya Chattopadhyay, Wei Xia, Stefano Soatto
2024	A*	`conf`	Bootstrapping Variational Information Pursuit with Large Language and Vision Models for Interpretable Image Classification. ICLR Aditya Chattopadhyay, Kwan Ho Ryan Chan, René Vidal
2024	A*	`conf`	PaCE: Parsimonious Concept Engineering for Large Language Models. NeurIPS Jinqi Luo, Tianjiao Ding, Kwan Ho Ryan Chan, Darshan Thaker, Aditya Chattopadhyay, Chris Callison-Burch, René Vidal
2024	J	`jnl`	PaCE: Parsimonious Concept Engineering for Large Language Models. CoRR Jinqi Luo, Tianjiao Ding, Kwan Ho Ryan Chan, Darshan Thaker, Aditya Chattopadhyay, Chris Callison-Burch, René Vidal
2024	A*	`conf`	Performance Bounds for Active Binary Testing with Information Maximization. ICML Aditya Chattopadhyay, Benjamin David Haeffele, René Vidal, Donald Geman
2023	A*	`conf`	Information Maximization Perspective of Orthogonal Matching Pursuit with Applications to Explainable AI. NeurIPS Aditya Chattopadhyay, Ryan Pilgrim, René Vidal
2023	J	`jnl`	Interpretable by Design: Learning Predictors by Composing Interpretable Queries. IEEE Trans. Pattern Anal. Mach. Intell. Aditya Chattopadhyay, Stewart Slocum, Benjamin D. Haeffele, René Vidal, Donald Geman
2023	A	`conf`	Learning Graph Variational Autoencoders with Constraints and Structured Priors for Conditional Indoor 3D Scene Generation. WACV Aditya Chattopadhyay, Xi Zhang, David Paul Wipf, Himanshu Arora, René Vidal
2023	J	`jnl`	Learning Interpretable Queries for Explainable Image Classification with Information Pursuit. CoRR Stefan Kolek, Aditya Chattopadhyay, Kwan Ho Ryan Chan, Héctor Andrade-Loarca, Gitta Kutyniok, René Vidal
2023	A*	`conf`	Variational Information Pursuit for Interpretable Predictions. ICLR Aditya Chattopadhyay, Kwan Ho Ryan Chan, Benjamin David Haeffele, Donald Geman, René Vidal
2023	J	`jnl`	Variational Information Pursuit for Interpretable Predictions. CoRR Aditya Chattopadhyay, Kwan Ho Ryan Chan, Benjamin D. Haeffele, Donald Geman, René Vidal
2023	J	`jnl`	Variational Information Pursuit with Large Language and Multimodal Models for Interpretable Predictions. CoRR Kwan Ho Ryan Chan, Aditya Chattopadhyay, Benjamin David Haeffele, René Vidal
2022	J	`jnl`	Interpretable by Design: Learning Predictors by Composing Interpretable Queries. CoRR Aditya Chattopadhyay, Stewart Slocum, Benjamin D. Haeffele, René Vidal, Donald Geman
2022	J	`jnl`	Structured Graph Variational Autoencoders for Indoor Furniture layout Generation. CoRR Aditya Chattopadhyay, Xi Zhang, David Paul Wipf, Himanshu Arora, René Vidal
2019	A*	`conf`	Neural Network Attributions: A Causal Perspective. ICML Aditya Chattopadhyay, Piyushi Manupriya, Anirban Sarkar, Vineeth N. Balasubramanian
2019	J	`jnl`	Neural Network Attributions: A Causal Perspective. CoRR Aditya Chattopadhyay, Piyushi Manupriya, Anirban Sarkar, Vineeth N. Balasubramanian
2018	A	`conf`	Grad-CAM++: Generalized Gradient-Based Visual Explanations for Deep Convolutional Networks. WACV Aditya Chattopadhyay, Anirban Sarkar, Prantik Howlader, Vineeth N. Balasubramanian
2017	J	`jnl`	Grad-CAM++: Generalized Gradient-based Visual Explanations for Deep Convolutional Networks. CoRR Aditya Chattopadhyay, Anirban Sarkar, Prantik Howlader, Vineeth N. Balasubramanian