Conference and Journal Publications

Google Scholar: Ronak Mehta

If you’re interested in a particular paper, that’s not easily available, feel free to reach out to me for a copy.

  • Identifying Feature, Parameter, and Sample Subsets in Machine Learning and Image Analysis
    Ronak Mehta
    Final Dissertation, University of Wisconsin-Madison.
    ProQuest | PDF

  • 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
    ICLR | code | video

  • Deep Unlearning via Randomized Conditionally Independent Hessians
    Ronak Mehta*, Sourav Pal*, Vikas Singh, Sathya Ravi
    Computer Vision and Pattern Recognition, CVPR 2022
    CVPR | 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
    ISBI

  • 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
    UAI | arXiv | code | video

  • Scaling Recurrent Models via Orthogonal Approximations in Tensor Trains
    Ronak Mehta, Rudrasis Chakraborty, Yunyang Xiong, Vikas Singh
    International Conference on Computer Vision, ICCV 2019
    ICCV

  • Resource Constrained Neural Network Architecture Search: Will a Submodularity Assumption Help?
    Yunyang Xiong, Ronak Mehta, Vikas Singh
    International Conference on Computer Vision, ICCV 2019
    ICCV

  • 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
    ICCV

  • Sampling-free Uncertainty Estimation in Gated Recurrent Units with Applications to Normative Modeling in Neuroimaging
    Seong Jae Hwang, Ronak Mehta, Hyunwoo J. Kim, Sterling C. Johnson, Vikas Singh
    Uncertainty in Artificial Intelligence, UAI 2019
    UAI

  • 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
    IPMI

  • 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
    QAM | arXiv | video

  • Robust Blind Deconvolution via Mirror Descent
    Sathya Ravi, Ronak Mehta, Vikas Singh
    International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2023
    ICASSP | arXiv