Viktor Reshniak

Publication Activity (10 Years)

Years Active: 2018-2024
Publications (10 Years): 14

Top Topics

Image Inpainting

Top Venues

Monte Carlo Methods Appl.

J. Comput. Appl. Math.

Publications

Yichuan Shi, Olivera Kotevska, Viktor Reshniak, Abhishek Singh, Ramesh Raskar
Dealing Doubt: Unveiling Threat Models in Gradient Inversion Attacks under Federated Learning, A Survey and Taxonomy. CoRR (2024)
Qian Gong, Chengzhu Zhang, Xin Liang, Viktor Reshniak, Jieyang Chen, Anand Rangarajan, Sanjay Ranka, Nicolas Vidal, Lipeng Wan, Paul Ullrich, Norbert Podhorszki, Robert Jacob, Scott Klasky
Spatiotemporally adaptive compression for scientific dataset with feature preservation - a case study on simulation data with extreme climate events analysis. CoRR (2024)
Qian Gong, Jieyang Chen, Ben Whitney, Xin Liang, Viktor Reshniak, Tania Banerjee, Jaemoon Lee, Anand Rangarajan, Lipeng Wan, Nicolas Vidal, Qing Liu, Ana Gainaru, Norbert Podhorszki, Richard Archibald, Sanjay Ranka, Scott Klasky
MGARD: A multigrid framework for high-performance, error-controlled data compression and refactoring. CoRR (2024)
Qian Gong, Chengzhu Zhang, Xin Liang, Viktor Reshniak, Jieyang Chen, Anand Rangarajan, Sanjay Ranka, Nicolas Vidal, Lipeng Wan, Paul Ullrich, Norbert Podhorszki, Robert Jacob, Scott Klasky
Spatiotemporally Adaptive Compression for Scientific Dataset with Feature Preservation - A Case Study on Simulation Data with Extreme Climate Events Analysis. e-Science (2023)
Qian Gong, Jieyang Chen, Ben Whitney, Xin Liang, Viktor Reshniak, Tania Banerjee, Jaemoon Lee, Anand Rangarajan, Lipeng Wan, Nicolas Vidal, Qing Liu, Ana Gainaru, Norbert Podhorszki, Richard Archibald, Sanjay Ranka, Scott Klasky
MGARD: A multigrid framework for high-performance, error-controlled data compression and refactoring. SoftwareX 24 (2023)
Viktor Reshniak
Dissipative residual layers for unsupervised implicit parameterization of data manifolds. CoRR (2022)
Viktor Reshniak, Clayton G. Webster
Robust Learning with Implicit Residual Networks. Mach. Learn. Knowl. Extr. 3 (1) (2021)
Massimiliano Lupo Pasini, Junqi Yin, Viktor Reshniak, Miroslav Stoyanov
Stable Anderson Acceleration for Deep Learning. CoRR (2021)
Viktor Reshniak, Jeremy Trageser, Clayton G. Webster
A Nonlocal Feature-Driven Exemplar-Based Approach for Image Inpainting. SIAM J. Imaging Sci. 13 (4) (2020)
Viktor Reshniak, Yuri A. Melnikov
Method of Green's Potentials for Elliptic PDEs in Domains with Random Apertures. J. Sci. Comput. 84 (3) (2020)
Viktor Reshniak, Abdul Q. M. Khaliq, David A. Voss
Slow-scale split-step tau-leap method for stiff stochastic chemical systems. J. Comput. Appl. Math. 361 (2019)
Viktor Reshniak, Clayton G. Webster
Robust learning with implicit residual networks. CoRR (2019)
Viktor Reshniak, Jeremy Trageser, Clayton G. Webster
A nonlocal feature-driven exemplar-based approach for image inpainting. CoRR (2019)
Harold A. Lay, Zane Colgin, Viktor Reshniak, Abdul Q. M. Khaliq
On the implementation of multilevel Monte Carlo simulation of the stochastic volatility and interest rate model using multi-GPU clusters. Monte Carlo Methods Appl. 24 (4) (2018)