- Phillip Lo, Yuehaw Khoo. Method of Moments for Estimation of Noisy Curves. SIMODS, 8(1):200-223, 2026.
- Anthony Coache, Sebastian Jaimungal. Robust Reinforcement Learning with Dynamic Distortion Risk Measures. SIMODS, 8(1):1-22, 2026.
- Giulio Biroli, Marc Mézard. Kernel Density Estimators in Large Dimensions. SIMODS, 8(1):46-76, 2026.
- Quanjun Lang, Jianfeng Lu 0001. Learning Memory Kernels in Generalized Langevin Equations. SIMODS, 8(1):141-166, 2026.
- Matthew King-Roskamp, Rustum Choksi, Tim Hoheisel. Data-Driven Priors in the Maximum Entropy on the Mean Method for Linear Inverse Problems. SIMODS, 8(1):108-140, 2026.
- Giovanni S. Alberti, Ernesto De Vito, Tapio Helin, Matti Lassas, Luca Ratti, Matteo Santacesaria. Learning Sparsity-Promoting Regularizers for Linear Inverse Problems. SIMODS, 8(1):167-199, 2026.
- Natalie S. Frank. A Notion of Uniqueness for the Adversarial Bayes Classifier. SIMODS, 8(1):77-107, 2026.
- Giacomo Turri, Vladimir Kostic, Pietro Novelli, Massimiliano Pontil. A Randomized Algorithm to Solve Reduced Rank Operator Regression. SIMODS, 8(1):23-45, 2026.
- Tamir Bendory, Nadav Dym, Dan Edidin, Arun Suresh. Phase Retrieval with Semialgebraic and ReLU Neural Network Priors. SIMODS, 7(4):1705-1728, 2025.
- Jason M. Altschuler, Kunal Talwar. Resolving the Mixing Time of the Langevin Algorithm to Its Stationary Distribution for Log-Concave Sampling. SIMODS, 7(3):993-1020, 2025.