Vishnu Suresh Lokhande

According to our database, Vishnu Suresh Lokhande authored at least 16 papers between 2019 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Craft: Cross-modal Aligned Features Improve Robustness of Prompt Tuning.

Jingchen Sun, Rohan Sharma, Vishnu Suresh Lokhande, Changyou Chen

CoRR, 2024

MultiEdits: Simultaneous Multi-Aspect Editing with Text-to-Image Diffusion Models.

Mingzhen Huang, Jialing Cai, Shan Jia, Vishnu Suresh Lokhande, Siwei Lyu

CoRR, 2024

ParallelEdits: Efficient Multi-Aspect Text-Driven Image Editing with Attention Grouping.

Mingzhen Huang, Jialing Cai, Shan Jia, Vishnu Suresh Lokhande, Siwei Lyu

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

Pooling Image Datasets with Multiple Covariate Shift and Imbalance.

Sotirios Panagiotis Chytas, Vishnu Suresh Lokhande, Vikas Singh

Proceedings of the Twelfth International Conference on Learning Representations, 2024

2023

Efficient Discrete Multi Marginal Optimal Transport Regularization.

Ronak Mehta, Jeffery Kline, Vishnu Suresh Lokhande, Glenn Fung, Vikas Singh

Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022

Towards Group Robustness in the presence of Partial Group Labels.

Vishnu Suresh Lokhande, Kihyuk Sohn, Jinsung Yoon, Madeleine Udell, Chen-Yu Lee, Tomas Pfister

CoRR, 2022

Equivariance Allows Handling Multiple Nuisance Variables When Analyzing Pooled Neuroimaging Datasets.

Vishnu Suresh Lokhande, Rudrasis Chakraborty, Sathya N. Ravi, Vikas Singh

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

2021

Graph reparameterizations for enabling 1000+ Monte Carlo iterations in Bayesian deep neural networks.

Jurijs Nazarovs, Ronak R. Mehta, Vishnu Suresh Lokhande, Vikas Singh

Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, 2021

Learning Invariant Representations using Inverse Contrastive Loss.

Aditya Kumar Akash, Vishnu Suresh Lokhande, Sathya N. Ravi, Vikas Singh

Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020

FairALM: Augmented Lagrangian Method for Training Fair Models with Little Regret.

Vishnu Suresh Lokhande, Aditya Kumar Akash, Sathya N. Ravi, Vikas Singh

Proceedings of the Computer Vision - ECCV 2020, 2020

Generating Accurate Pseudo-Labels in Semi-Supervised Learning and Avoiding Overconfident Predictions via Hermite Polynomial Activations.

Vishnu Suresh Lokhande, Songwong Tasneeyapant, Abhay Venkatesh, Sathya N. Ravi, Vikas Singh

Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020

Accelerating Column Generation via Flexible Dual Optimal Inequalities with Application to Entity Resolution.

Vishnu Suresh Lokhande, Shaofei Wang, Maneesh Singh, Julian Yarkony

Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019

End-to-end Training of CNN-CRF via Differentiable Dual-Decomposition.

Shaofei Wang, Vishnu Suresh Lokhande, Maneesh Singh, Konrad P. Körding, Julian Yarkony

CoRR, 2019

Active Learning with Importance Sampling.

Muni Sreenivas Pydi, Vishnu Suresh Lokhande

CoRR, 2019

Generating Accurate Pseudo-labels via Hermite Polynomials for SSL Confidently.

Vishnu Suresh Lokhande, Sathya N. Ravi, Songwong Tasneeyapant, Abhay Venkatesh, Vikas Singh

CoRR, 2019

Explicitly Imposing Constraints in Deep Networks via Conditional Gradients Gives Improved Generalization and Faster Convergence.

Sathya N. Ravi, Tuan Dinh, Vishnu Suresh Lokhande, Vikas Singh

Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019