Low-Rank Tucker Decomposition of Large Tensors Using TensorSketch. - Osman Asif Malik; Stephen Becker (NeurIPS, 2018)

Tensor Graph Convolutional Networks for Prediction on Dynamic Graphs. - Osman Asif Malik; Shashanka Ubaru; Lior Horesh; Misha E. Kilmer; Haim Avron (CoRR, 2019)

Guarantees for the Kronecker Fast Johnson-Lindenstrauss Transform Using a Coherence and Sampling Argument. - Osman Asif Malik; Stephen Becker (CoRR, 2019)

Fast randomized matrix and tensor interpolative decomposition using CountSketch. - Osman Asif Malik; Stephen Becker (Adv. Comput. Math., 2020)

Binary Matrix Factorization on Special Purpose Hardware. - Osman Asif Malik; Hayato Ushijima-Mwesigwa; Arnab Roy 001; Avradip Mandal; Indradeep Ghosh (CoRR, 2020)

A Sampling-Based Method for Tensor Ring Decomposition. - Osman Asif Malik; Stephen Becker (ICML, 2021)

Dynamic Graph Convolutional Networks Using the Tensor M-Product. - Osman Asif Malik; Shashanka Ubaru; Lior Horesh; Misha E. Kilmer; Haim Avron (SDM, 2021)

Superresolution Photoacoustic Tomography Using Random Speckle Illumination and Second Order Moments. - Osman Asif Malik; Venkatalakshmi Vyjayanthi Narumanchi; Stephen Becker; Todd W. Murray (WASPAA, 2021)

More Efficient Sampling for Tensor Decomposition. - Osman Asif Malik (CoRR, 2021)

Randomization of approximate bilinear computation for matrix multiplication. - Osman Asif Malik; Stephen Becker (Int. J. Comput. Math. Comput. Syst. Theory, 2021)

More Efficient Sampling for Tensor Decomposition With Worst-Case Guarantees. - Osman Asif Malik (ICML, 2022)

Fast Algorithms for Monotone Lower Subsets of Kronecker Least Squares Problems. - Osman Asif Malik; Yiming Xu; Nuojin Cheng; Stephen Becker; Alireza Doostan; Akil Narayan 001 (CoRR, 2022)

Quadrature Sampling of Parametric Models with Bi-fidelity Boosting. - Nuojin Cheng; Osman Asif Malik; Yiming Xu; Stephen Becker; Alireza Doostan; Akil Narayan 001 (CoRR, 2022)

Sampling-Based Decomposition Algorithms for Arbitrary Tensor Networks. - Osman Asif Malik; Vivek Bharadwaj; Riley Murray (CoRR, 2022)

Fast Exact Leverage Score Sampling from Khatri-Rao Products with Applications to Tensor Decomposition. - Vivek Bharadwaj; Osman Asif Malik; Riley Murray; Laura Grigori; Aydin Buluç; James Demmel (NeurIPS, 2023)

Construction of Hierarchically Semi-Separable matrix Representation using Adaptive Johnson-Lindenstrauss Sketching. - Yotam Yaniv; Osman Asif Malik; Pieter Ghysels; Xiaoye S. Li (CoRR, 2023)

Randomized Numerical Linear Algebra : A Perspective on the Field With an Eye to Software. - Riley Murray; James Demmel; Michael W. Mahoney; N. Benjamin Erichson; Maksim Melnichenko; Osman Asif Malik; Laura Grigori; Piotr Luszczek; Michal Derezinski; Miles E. Lopes; Tianyu Liang; Hengrui Luo; et al. (CoRR, 2023)

Bi-fidelity Variational Auto-encoder for Uncertainty Quantification. - Nuojin Cheng; Osman Asif Malik; Stephen Becker; Alireza Doostan (CoRR, 2023)

rBahadur: efficient simulation of structured high-dimensional genotype data with applications to assortative mating. - Richard Border; Osman Asif Malik (BMC Bioinform., 2023)

Efficient Leverage Score Sampling for Tensor Train Decomposition. - Vivek Bharadwaj; Beheshteh T. Rakhshan; Osman Asif Malik; Guillaume Rabusseau (NeurIPS, 2024)

Distributed-Memory Randomized Algorithms for Sparse Tensor CP Decomposition. - Vivek Bharadwaj; Osman Asif Malik; Riley Murray; Aydin Buluç; James Demmel (SPAA, 2024)

Learning Physics for Unveiling Hidden Earthquake Ground Motions via Conditional Generative Modeling. - Pu Ren; Rie Nakata; Maxime Lacour; Ilan Naiman; Nori Nakata; Jialin Song; Zhengfa Bi; Osman Asif Malik; Dmitriy Morozov; Omri Azencot; N. Benjamin Erichson; Michael W. Mahoney (CoRR, 2024)

Subsampling of Parametric Models with Bifidelity Boosting. - Nuojin Cheng; Osman Asif Malik; Yiming Xu; Stephen Becker; Alireza Doostan; Akil Narayan 001 (SIAM/ASA J. Uncertain. Quantification, 2024)