| 2025 | ICASSP | A Quantitative Metric Selection Approach for Time-series Forecasting Foundation Models. | Hongjie Chen, Akshay Mehra, Josh Kimball, Sungchul Kim |
| 2025 | ICML | DPCore: Dynamic Prompt Coreset for Continual Test-Time Adaptation. | Yunbei Zhang, Akshay Mehra, Shuaicheng Niu, Jihun Hamm |
| 2025 | WACV | OT-VP: Optimal Transport-Guided Visual Prompting for Test-Time Adaptation. | Yunbei Zhang, Akshay Mehra, Jihun Hamm |
| 2024 | CVPR | Test-time Assessment of a Model's Performance on Unseen Domains via Optimal Transport. | Akshay Mehra, Yunbei Zhang, Jihun Hamm |
| 2024 | WACV | On the Fly Neural Style Smoothing for Risk-Averse Domain Generalization. | Akshay Mehra, Yunbei Zhang, Bhavya Kailkhura, Jihun Hamm |
| 2022 | ECCV | A Spectral View of Randomized Smoothing Under Common Corruptions: Benchmarking and Improving Certified Robustness. | Jiachen Sun, Akshay Mehra, Bhavya Kailkhura, Pin-Yu Chen, Dan Hendrycks, Jihun Hamm, Z. Morley Mao |
| 2021 | ACML | Penalty Method for Inversion-Free Deep Bilevel Optimization. | Akshay Mehra, Jihun Hamm |
| 2021 | CVPR | How Robust Are Randomized Smoothing Based Defenses to Data Poisoning? | Akshay Mehra, Bhavya Kailkhura, Pin-Yu Chen, Jihun Hamm |