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)

Enhanced Regularizers for Attributional Robustness. - Anindya Sarkar; Anirban Sarkar 001; Vineeth N. Balasubramanian (AAAI, 2021)

Adversarial Robustness without Adversarial Training: A Teacher-Guided Curriculum Learning Approach. - Anindya Sarkar; Anirban Sarkar 001; Sowrya Gali; Vineeth N. Balasubramanian (NeurIPS, 2021)

Inducing Semantic Grouping of Latent Concepts for Explanations: An Ante-Hoc Approach. - Anirban Sarkar 001; Deepak Vijaykeerthy; Anindya Sarkar; Vineeth N. Balasubramanian (CoRR, 2021)

Get Fooled for the Right Reason: Improving Adversarial Robustness through a Teacher-guided Curriculum Learning Approach. - Anindya Sarkar; Anirban Sarkar 001; Sowrya Gali; Vineeth N. Balasubramanian (CoRR, 2021)

A Framework for Learning Ante-hoc Explainable Models via Concepts. - Anirban Sarkar 001; Deepak Vijaykeerthy; Anindya Sarkar; Vineeth N. Balasubramanian (CVPR, 2022)

Leveraging Test-Time Consensus Prediction for Robustness against Unseen Noise. - Anindya Sarkar; Anirban Sarkar 001; Vineeth N. Balasubramanian (WACV, 2022)