Jeet Mohapatra

According to our database1, Jeet Mohapatra authored at least 9 papers between 2018 and 2024.

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Bibliography

2024
What Would Gauss Say About Representations? Probing Pretrained Image Models using Synthetic Gaussian Benchmarks.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

2022
SynBench: Task-Agnostic Benchmarking of Pretrained Representations using Synthetic Data.
CoRR, 2022

Revisiting Contrastive Learning through the Lens of Neighborhood Component Analysis: an Integrated Framework.
Proceedings of the International Conference on Machine Learning, 2022

2021
Hidden Cost of Randomized Smoothing.
Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

2020
Rethinking Randomized Smoothing for Adversarial Robustness.
CoRR, 2020

Higher-Order Certification For Randomized Smoothing.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Towards Verifying Robustness of Neural Networks Against A Family of Semantic Perturbations.
Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020

2019
Towards Verifying Robustness of Neural Networks Against Semantic Perturbations.
CoRR, 2019

2018
Optimal Gossip Algorithms for Exact and Approximate Quantile Computations.
Proceedings of the 2018 ACM Symposium on Principles of Distributed Computing, 2018


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