Piratla, Vihari

12 publications

TMLR 2025 Model Guidance via Robust Feature Attribution Mihnea Ghitu, Vihari Piratla, Matthew Robert Wicker

NeurIPSW 2024 LLMs on Interactive Feature Collections with Implicit Look-Ahead Strategies Juyeon Heo, Vihari Piratla, Kyunghyun Lee, Hyonkeun Joh, Adrian Weller

NeurIPS 2023 Certification of Distributional Individual Fairness Matthew Wicker, Vihari Piratla, Adrian Weller

NeurIPSW 2023 Estimation of Concept Explanations Should Be Uncertainty Aware Vihari Piratla, Juyeon Heo, Sukriti Singh, Adrian Weller

UAI 2023 Human-in-the-Loop Mixup Katherine M. Collins, Umang Bhatt, Weiyang Liu, Vihari Piratla, Ilia Sucholutsky, Bradley Love, Adrian Weller

NeurIPS 2023 Use Perturbations When Learning from Explanations Juyeon Heo, Vihari Piratla, Matthew Wicker, Adrian Weller

NeurIPSW 2023 Use Perturbations When Learning from Explanations Juyeon Heo, Vihari Piratla, Matthew Wicker, Adrian Weller

ICLR 2022 Focus on the Common Good: Group Distributional Robustness Follows Vihari Piratla, Praneeth Netrapalli, Sunita Sarawagi

NeurIPS 2021 Active Assessment of Prediction Services as Accuracy Surface over Attribute Combinations Vihari Piratla, Soumen Chakrabarti, Sunita Sarawagi

NeurIPS 2021 Training for the Future: A Simple Gradient Interpolation Loss to Generalize Along Time Anshul Nasery, Soumyadeep Thakur, Vihari Piratla, Abir De, Sunita Sarawagi

ICML 2020 Efficient Domain Generalization via Common-Specific Low-Rank Decomposition Vihari Piratla, Praneeth Netrapalli, Sunita Sarawagi

ICLR 2018 Generalizing Across Domains via Cross-Gradient Training Shiv Shankar, Vihari Piratla, Soumen Chakrabarti, Siddhartha Chaudhuri, Preethi Jyothi, Sunita Sarawagi