A Chebyshev-Accelerated Primal-Dual Method for Distributed Optimization. - Jacob H. Seidman; Mahyar Fazlyab; George J. Pappas; Victor M. Preciado (CDC, 2018)

Robust Deep Learning as Optimal Control: Insights and Convergence Guarantees. - Jacob H. Seidman; Mahyar Fazlyab; Victor M. Preciado; George J. Pappas (L4DC, 2020)

A Control-Theoretic Approach to Analysis and Parameter Selection of Douglas-Rachford Splitting. - Jacob H. Seidman; Mahyar Fazlyab; Victor M. Preciado; George J. Pappas (IEEE Control. Syst. Lett., 2020)

Gaussian Process Port-Hamiltonian Systems: Bayesian Learning with Physics Prior. - Thomas Beckers 001; Jacob H. Seidman; Paris Perdikaris; George J. Pappas (CDC, 2022)

NOMAD: Nonlinear Manifold Decoders for Operator Learning. - Jacob H. Seidman; Georgios Kissas; Paris Perdikaris; George J. Pappas (NeurIPS, 2022)

Random Weight Factorization Improves the Training of Continuous Neural Representations. - Sifan Wang; Hanwen Wang; Jacob H. Seidman; Paris Perdikaris (CoRR, 2022)

Learning Operators with Coupled Attention. - Georgios Kissas; Jacob H. Seidman; Leonardo Ferreira Guilhoto; Victor M. Preciado; George J. Pappas; Paris Perdikaris (J. Mach. Learn. Res., 2022)

Variational Autoencoding Neural Operators. - Jacob H. Seidman; Georgios Kissas; George J. Pappas; Paris Perdikaris (ICML, 2023)

Bridging Operator Learning and Conditioned Neural Fields: A Unifying Perspective. - Sifan Wang; Jacob H. Seidman; Shyam Sankaran; Hanwen Wang; George J. Pappas; Paris Perdikaris (CoRR, 2024)

Score Neural Operator: A Generative Model for Learning and Generalizing Across Multiple Probability Distributions. - Xinyu Liao; Aoyang Qin; Jacob H. Seidman; Junqi Wang; Wei Wang; Paris Perdikaris (CoRR, 2024)

CViT: Continuous Vision Transformer for Operator Learning. - Sifan Wang; Jacob H. Seidman; Shyam Sankaran; Hanwen Wang; George J. Pappas; Paris Perdikaris (ICLR, 2025)