Aditya Chattopadhyay
Aditya Chattopadhyay
Johns Hopkins University
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Cited by
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Grad-cam++: Generalized gradient-based visual explanations for deep convolutional networks
A Chattopadhay, A Sarkar, P Howlader, VN Balasubramanian
2018 IEEE winter conference on applications of computer vision (WACV), 839-847, 2018
Neural network attributions: A causal perspective
A Chattopadhyay, P Manupriya, A Sarkar, VN Balasubramanian
International Conference on Machine Learning, 981-990, 2019
Role of urea–aromatic stacking interactions in stabilizing the aromatic residues of the protein in urea-induced denatured state
S Goyal, A Chattopadhyay, K Kasavajhala, UD Priyakumar
Journal of the American Chemical Society 139 (42), 14931-14946, 2017
Interpretable by design: Learning predictors by composing interpretable queries
A Chattopadhyay, S Slocum, BD Haeffele, R Vidal, D Geman
IEEE Transactions on Pattern Analysis and Machine Intelligence 45 (6), 7430-7443, 2022
Quantifying task complexity through generalized information measures
A Chattopadhyay, BD Haeffele, D Geman, R Vidal
Energetic, structural and dynamic properties of nucleobase-urea interactions that aid in urea assisted RNA unfolding
T Jaganade, A Chattopadhyay, NM Pazhayam, UD Priyakumar
Scientific Reports 9 (1), 8805, 2019
Variational information pursuit for interpretable predictions
A Chattopadhyay, KHR Chan, BD Haeffele, D Geman, R Vidal
The Eleventh International Conference on Learning Representations, 2023
Learning graph variational autoencoders with constraints and structured priors for conditional indoor 3D scene generation
A Chattopadhyay, X Zhang, DP Wipf, H Arora, R Vidal
Proceedings of the IEEE/CVF winter conference on applications of computer …, 2023
A probabilistic framework for constructing temporal relations in replica exchange molecular trajectories
A Chattopadhyay, M Zheng, MP Waller, UD Priyakumar
Journal of chemical theory and computation 14 (7), 3365-3380, 2018
Urea-water solvation of protein side chain models
T Jaganade, A Chattopadhyay, S Raghunathan, UD Priyakumar
Journal of Molecular Liquids 311, 113191, 2020
Information maximization perspective of orthogonal matching pursuit with applications to explainable ai
A Chattopadhyay, R Pilgrim, R Vidal
Advances in Neural Information Processing Systems 36, 2024
Learning Interpretable Queries for Explainable Image Classification with Information Pursuit
S Kolek, A Chattopadhyay, KHR Chan, H Andrade-Loarca, G Kutyniok, ...
arXiv preprint arXiv:2312.11548, 2023
Performance Bounds for Active Binary Testing with Information Maximization
A Chattopadhyay, BD Haeffele, R Vidal, D Geman
Bootstrapping Variational Information Pursuit with Foundation Models for Interpretable Image Classification
A Chattopadhyay, KHR Chan, R Vidal
The Twelfth International Conference on Learning Representations, 2023
Variational Information Pursuit with Large Language and Multimodal Models for Interpretable Predictions
KHR Chan, A Chattopadhyay, BD Haeffele, R Vidal
arXiv preprint arXiv:2308.12562, 2023
A probabilistic framework for constructing temporal relations in Monte Carlo trajectories
A Chattopadhyay
International Institute of Information Technology, 2018
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