Compressive through-focus wavefield imaging. - Edwin A. Marengo; Oren Mangoubi (Computational Imaging, 2011)

Towards optimal convex combination rules for gossiping. - Oren Mangoubi; Shaoshuai Mou; Ji Liu 001; A. Stephen Morse (ACC, 2013)

Rapid Mixing of Geodesic Walks on Manifolds with Positive Curvature. - Oren Mangoubi; Aaron Smith (CoRR, 2016)

Convex Optimization with Nonconvex Oracles. - Oren Mangoubi; Nisheeth K. Vishnoi (CoRR, 2017)

Convex Optimization with Unbounded Nonconvex Oracles using Simulated Annealing. - Oren Mangoubi; Nisheeth K. Vishnoi (COLT, 2018)

Dimensionally Tight Bounds for Second-Order Hamiltonian Monte Carlo. - Oren Mangoubi; Nisheeth K. Vishnoi (NeurIPS, 2018)

Dimensionally Tight Running Time Bounds for Second-Order Hamiltonian Monte Carlo. - Oren Mangoubi; Nisheeth K. Vishnoi (CoRR, 2018)

Does Hamiltonian Monte Carlo mix faster than a random walk on multimodal densities? - Oren Mangoubi; Natesh S. Pillai; Aaron Smith (CoRR, 2018)

Mixing of Hamiltonian Monte Carlo on strongly log-concave distributions 2: Numerical integrators. - Oren Mangoubi; Aaron Smith (AISTATS, 2019)

Nonconvex sampling with the Metropolis-adjusted Langevin algorithm. - Oren Mangoubi; Nisheeth K. Vishnoi (COLT, 2019)

Faster Polytope Rounding, Sampling, and Volume Computation via a Sub-Linear Ball Walk. - Oren Mangoubi; Nisheeth K. Vishnoi (FOCS, 2019)

Online sampling from log-concave distributions. - Holden Lee; Oren Mangoubi; Nisheeth K. Vishnoi (NeurIPS, 2019)

Faster algorithms for polytope rounding, sampling, and volume computation via a sublinear "Ball Walk". - Oren Mangoubi; Nisheeth K. Vishnoi (CoRR, 2019)

A Second-order Equilibrium in Nonconvex-Nonconcave Min-max Optimization: Existence and Algorithm. - Oren Mangoubi; Nisheeth K. Vishnoi (CoRR, 2020)

A Provably Convergent and Practical Algorithm for Min-max Optimization with Applications to GANs. - Oren Mangoubi; Sushant Sachdeva; Nisheeth K. Vishnoi (CoRR, 2020)

Sync-Switch: Hybrid Parameter Synchronization for Distributed Deep Learning. - Shijian Li; Oren Mangoubi; Lijie Xu; Tian Guo 001 (ICDCS, 2021)

DAC-ML: Domain Adaptable Continuous Meta-Learning for Urban Dynamics Prediction. - Xin Zhang 098; Yanhua Li; Xun Zhou 001; Oren Mangoubi; Ziming Zhang; Vincent Filardi; Jun Luo 007 (ICDM, 2021)

Greedy adversarial equilibrium: an efficient alternative to nonconvex-nonconcave min-max optimization. - Oren Mangoubi; Nisheeth K. Vishnoi (STOC, 2021)

Sampling from Log-Concave Distributions with Infinity-Distance Guarantees and Applications to Differentially Private Optimization. - Oren Mangoubi; Nisheeth K. Vishnoi (CoRR, 2021)

Simple conditions for metastability of continuous Markov chains. - Oren Mangoubi; Natesh S. Pillai; Aaron Smith (J. Appl. Probab., 2021)

Private Matrix Approximation and Geometry of Unitary Orbits. - Oren Mangoubi; Yikai Wu 001; Satyen Kale; Abhradeep Thakurta; Nisheeth K. Vishnoi (COLT, 2022)

A Convergent and Dimension-Independent Min-Max Optimization Algorithm. - Vijay Keswani; Oren Mangoubi; Sushant Sachdeva; Nisheeth K. Vishnoi (ICML, 2022)

Predicting MXene Properties via Machine Learning. - Eric W. Vertina; N. Aaron Deskins; Emily Sutherland; Oren Mangoubi (ICMLA, 2022)

Sampling from Log-Concave Distributions with Infinity-Distance Guarantees. - Oren Mangoubi; Nisheeth K. Vishnoi (NeurIPS, 2022)

Re-Analyze Gauss: Bounds for Private Matrix Approximation via Dyson Brownian Motion. - Oren Mangoubi; Nisheeth K. Vishnoi (NeurIPS, 2022)

Faster Sampling from Log-Concave Distributions over Polytopes via a Soft-Threshold Dikin Walk. - Oren Mangoubi; Nisheeth K. Vishnoi (CoRR, 2022)

Private Covariance Approximation and Eigenvalue-Gap Bounds for Complex Gaussian Perturbations. - Oren Mangoubi; Nisheeth K. Vishnoi (COLT, 2023)

Sampling from Structured Log-Concave Distributions via a Soft-Threshold Dikin Walk. - Oren Mangoubi; Nisheeth K. Vishnoi (NeurIPS, 2023)

Faster Sampling from Log-Concave Densities over Polytopes via Efficient Linear Solvers. - Oren Mangoubi; Nisheeth K. Vishnoi (ICLR, 2024)

Singular Subspace Perturbation Bounds via Rectangular Random Matrix Diffusions. - Peiyao Lai; Oren Mangoubi (ICLR, 2025)

Private Low-Rank Approximation for Covariance Matrices, Dyson Brownian Motion, and Eigenvalue-Gap Bounds for Gaussian Perturbations. - Oren Mangoubi; Nisheeth K. Vishnoi (J. ACM, 2025)

Efficient Diffusion Models for Symmetric Manifolds. - Oren Mangoubi; Neil He; Nisheeth K. Vishnoi (CoRR, 2025)