Research Projects and Publications
Efficient Discrete Multi Marginal Optimal Transport Regularization.
Ronak Mehta, Jeffery Kline, Vishnu Suresh Lokhande, Glenn Fung, Vikas Singh.
(top 25%) International Conference on Learning Representations, ICLR 2023.
[Paper]
Deep Unlearning via Randomized Conditionally Independent Hessians.
Ronak Mehta, Sourav Pal, Vikas Singh, Sathya Ravi.
Computer Vision and Pattern Recognition, CVPR 2022.
[Webpage]
[Paper]
[Code]
Investigating Functional Brain Network Abnormalities via Differential Covariance Trajectory Analysis and Scan Statistics.
Anita Sinha, Ronak Mehta, Veena Nair, Rasmus Birn, Vikas Singh, Vivek Prabhakaran.
International Symposium on Biomedical Imaging, ISBI 2022.
[Paper]
Graph Reparameterizations for Enabling 1000+ Monte Carlo Iterations in Bayesian Deep Neural Networks.
Yuri Nazarov, Ronak Mehta, Vishnu Lokhande, Vikas Singh.
Uncertainty in Artificial Intelligence, UAI 2021.
[Paper]
Scaling Recurrent Models via Orthogonal Approximations in Tensor Trains.
Ronak Mehta, Rudrasis Chakraborty, Yunyang Xiong, Vikas Singh.
International Conference on Computer Vision, ICCV 2019.
[Paper]
Resource Constrained Neural Network Architecture Search: Will a Submodularity Assumption Help?
Yunyang Xiong, Ronak Mehta, Vikas Singh.
International Conference on Computer Vision, ICCV 2019.
[Paper]
DUAL-GLOW: Conditional Flow-Based Generative Model for Modality Transfer.
Haoliang Sun, Ronak Mehta, Hao H. Zhou, Zhichun Huang, Sterling C. Johnson, Vivek Prabhakaran, Vikas Singh.
International Conference on Computer Vision, ICCV 2019.
[Paper]
Sampling-free Uncertainty Estimation in Gated Recurrent Units with Applications to Normative Modeling in Neuroimaging.
Seong Jae Hwang, Ronak R. Mehta, Hyunwoo J. Kim, Sterling C. Johnson, Vikas Singh.
Uncertainty in Artificial Intelligence, UAI 2019.
[Paper]
On Training Deep 3D CNN Models with Dependent Samples in Neuroimaging.
Yunyang Xiong, Hyunwoo J. Kim, Bhargav Tangirala, Ronak Mehta, Sterling C. Johnson, Vikas Singh.
Information Processing in Medical Imaging, IPMI 2019.
[Paper]
Finding Differentially Covarying Needles in a Temporally Evolving Haystack: A Scan Statistics Perspective.
Ronak Mehta, Hyunwoo Kim, Shulei Wang, Sterling Johnson, Ming Yuan, Vikas Singh.
Quart. Appl. Math. 77 (2018), 357-398
[Webpage] [Paper] [Video]
Robust Blind Deconvolution via Mirror Descent.
Sathya Ravi, Ronak Mehta, Vikas Singh.
[Paper]
Coursework
For a list of courses I've taken during my time at Wisconsin, and selected courses from my time in Ann Arbor, click here.
For an (incomplete) list of course projects I've worked on, click here.
Contact Me
Ronak Mehta
Office 5770
Medical Sciences Center, UW-Madison
1300 University Ave.
Madison, WI 53706
Email: [ronakrm] at [cs][wisc][edu]