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Deep Unlearning via Randomized Conditionally Independent Hessians



Ronak Mehta , Sourav Pal , Vikas Singh , Sathya N. Ravi

* Accepted to IEEE Computer Vision and Pattern Recognition, CVPR 2022 

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Equivariance Allows Handling Multiple Nuisance Variables When Analyzing Pooled Neuroimaging Datasets



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

* Accepted at 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) 

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Graph Reparameterizations for Enabling 1000+ Monte Carlo Iterations in Bayesian Deep Neural Networks



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


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Mixed Effects Neural ODE: A Variational Approximation for Analyzing the Dynamics of Panel Data



Jurijs Nazarovs , Rudrasis Chakraborty , Songwong Tasneeyapant , Sathya N. Ravi , Vikas Singh


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Forward Operator Estimation in Generative Models with Kernel Transfer Operators



Zhichun Huang , Rudrasis Chakraborty , Vikas Singh


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You Only Sample (Almost) Once: Linear Cost Self-Attention Via Bernoulli Sampling



Zhanpeng Zeng , Yunyang Xiong , Sathya N. Ravi , Shailesh Acharya , Glenn Fung , Vikas Singh

* Proceedings of the 38th ICML (2021) 

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Neural TMDlayer: Modeling Instantaneous flow of features via SDE Generators



Zihang Meng , Vikas Singh , Sathya N. Ravi


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An Online Riemannian PCA for Stochastic Canonical Correlation Analysis



Zihang Meng , Rudrasis Chakraborty , Vikas Singh


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Connecting What to Say With Where to Look by Modeling Human Attention Traces



Zihang Meng , Licheng Yu , Ning Zhang , Tamara Berg , Babak Damavandi , Vikas Singh , Amy Bearman


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Simpler Certified Radius Maximization by Propagating Covariances



Xingjian Zhen , Rudrasis Chakraborty , Vikas Singh

* This paper has been accepted by CVPR 2021 as an oral presentation. An introduction video can be found: https://youtu.be/m1ya2oNf5iE 

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