- Léon Zheng, Elisa Riccietti, Rémi Gribonval. Efficient Identification of Butterfly Sparse Matrix Factorizations. SIMODS, 5(1):22-49, March 2023.
- Wenyu Chen, Mathias Drton, Ali Shojaie. Causal Structural Learning via Local Graphs. SIMODS, 5(2):280-305, June 2023.
- Philip S. Chodrow, Nicole Eikmeier, Jamie Haddock. Nonbacktracking Spectral Clustering of Nonuniform Hypergraphs. SIMODS, 5(2):251-279, June 2023.
- Christian Bayer 0001, Peter K. Friz, Nikolas Tapia. Stability of Deep Neural Networks via Discrete Rough Paths. SIMODS, 5(1):50-76, March 2023.
- Sebastian Neumayer, Alexis Goujon, Pakshal Bohra, Michael Unser. Approximation of Lipschitz Functions Using Deep Spline Neural Networks. SIMODS, 5(2):306-322, June 2023.
- Adam Li, Ronan Perry, Chester Huynh, Tyler M. Tomita, Ronak Mehta, Jesús Arroyo, Jesse Patsolic, Benjamin Falk, Sridevi V. Sarma, Joshua T. Vogelstein. Manifold Oblique Random Forests: Towards Closing the Gap on Convolutional Deep Networks. SIMODS, 5(1):77-96, March 2023.
- Guillaume Huguet, Alexander Tong 0001, Bastian Rieck, Jessie Huang, Manik Kuchroo, Matthew J. Hirn, Guy Wolf, Smita Krishnaswamy. Time-Inhomogeneous Diffusion Geometry and Topology. SIMODS, 5(2):346-372, June 2023.
- Attila Lovas, Iosif Lytras, Miklós Rásonyi, Sotirios Sabanis. Taming Neural Networks with TUSLA: Nonconvex Learning via Adaptive Stochastic Gradient Langevin Algorithms. SIMODS, 5(2):323-345, June 2023.
- Francesco Tudisco, Desmond J. Higham. Core-Periphery Detection in Hypergraphs. SIMODS, 5(1):1-21, March 2023.
- Martin Molina-Fructuoso, Ryan W. Murray. Tukey Depths and Hamilton-Jacobi Differential Equations. SIMODS, 4(2):604-633, 2022.