Sumukh K. Aithal

Publication Activity (10 Years)

Years Active: 2020-2024
Publications (10 Years): 9

Top Topics

Class Imbalanced Data

Domain Adaptation

Top Venues

NeurIPS (Competition and Demos)

Publications

Sumukh K. Aithal, Pratyush Maini, Zachary C. Lipton, J. Zico Kolter
Understanding Hallucinations in Diffusion Models through Mode Interpolation. CoRR (2024)
Sumukh K. Aithal, Anirudh Goyal, Alex Lamb, Yoshua Bengio, Michael Mozer
Leveraging the Third Dimension in Contrastive Learning. CoRR (2023)
Harsh Rangwani, Sumukh K. Aithal, Mayank Mishra, Arihant Jain, Venkatesh Babu Radhakrishnan
A Closer Look at Smoothness in Domain Adversarial Training. ICML (2022)
Harsh Rangwani, Sumukh K. Aithal, Mayank Mishra, Arihant Jain, R. Venkatesh Babu
A Closer Look at Smoothness in Domain Adversarial Training. CoRR (2022)
Harsh Rangwani, Sumukh K. Aithal, Mayank Mishra, Venkatesh Babu R.
Escaping Saddle Points for Effective Generalization on Class-Imbalanced Data. NeurIPS (2022)
Harsh Rangwani, Sumukh K. Aithal, Mayank Mishra, R. Venkatesh Babu
Escaping Saddle Points for Effective Generalization on Class-Imbalanced Data. CoRR (2022)
Harsh Rangwani, Arihant Jain, Sumukh K. Aithal, R. Venkatesh Babu
VAADA: Submodular Subset Selection for Virtual Adversarial Active Domain Adaptation. ICCV (2021)
Harsh Rangwani, Arihant Jain, Sumukh K. Aithal, R. Venkatesh Babu
VAADA: Submodular Subset Selection for Virtual Adversarial Active Domain Adaptation. CoRR (2021)
Yiding Jiang, Parth Natekar, Manik Sharma, Sumukh K. Aithal, Dhruva Kashyap, Natarajan Subramanyam, Carlos Lassance, Daniel M. Roy, Gintare Karolina Dziugaite, Suriya Gunasekar, Isabelle Guyon, Pierre Foret, Scott Yak, Hossein Mobahi, Behnam Neyshabur, Samy Bengio
Methods and Analysis of The First Competition in Predicting Generalization of Deep Learning. NeurIPS (Competition and Demos) (2020)