Jacob H. Seidman

Publication Activity (10 Years)

Years Active: 2018-2024
Publications (10 Years): 14

Top Topics

Bayesian Learning

Top Venues

IEEE Control. Syst. Lett.

Publications

Sifan Wang, Jacob H. Seidman, Shyam Sankaran, Hanwen Wang, George J. Pappas, Paris Perdikaris
Bridging Operator Learning and Conditioned Neural Fields: A Unifying Perspective. CoRR (2024)
Jacob H. Seidman, Georgios Kissas, George J. Pappas, Paris Perdikaris
Variational Autoencoding Neural Operators. ICML (2023)
Thomas Beckers, Jacob H. Seidman, Paris Perdikaris, George J. Pappas
Gaussian Process Port-Hamiltonian Systems: Bayesian Learning with Physics Prior. CoRR (2023)
Jacob H. Seidman, Georgios Kissas, George J. Pappas, Paris Perdikaris
Variational Autoencoding Neural Operators. CoRR (2023)
Thomas Beckers, Jacob H. Seidman, Paris Perdikaris, George J. Pappas
Gaussian Process Port-Hamiltonian Systems: Bayesian Learning with Physics Prior. CDC (2022)
Jacob H. Seidman, Georgios Kissas, Paris Perdikaris, George J. Pappas
NOMAD: Nonlinear Manifold Decoders for Operator Learning. CoRR (2022)
Sifan Wang, Hanwen Wang, Jacob H. Seidman, Paris Perdikaris
Random Weight Factorization Improves the Training of Continuous Neural Representations. CoRR (2022)
Georgios Kissas, Jacob H. Seidman, Leonardo Ferreira Guilhoto, Victor M. Preciado, George J. Pappas, Paris Perdikaris
Learning Operators with Coupled Attention. J. Mach. Learn. Res. 23 (2022)
Jacob H. Seidman, Georgios Kissas, Paris Perdikaris, George J. Pappas
NOMAD: Nonlinear Manifold Decoders for Operator Learning. NeurIPS (2022)
Georgios Kissas, Jacob H. Seidman, Leonardo Ferreira Guilhoto, Victor M. Preciado, George J. Pappas, Paris Perdikaris
Learning Operators with Coupled Attention. CoRR (2022)
Jacob H. Seidman, Mahyar Fazlyab, Victor M. Preciado, George J. Pappas
A Control-Theoretic Approach to Analysis and Parameter Selection of Douglas-Rachford Splitting. IEEE Control. Syst. Lett. 4 (1) (2020)
Jacob H. Seidman, Mahyar Fazlyab, Victor M. Preciado, George J. Pappas
Robust Deep Learning as Optimal Control: Insights and Convergence Guarantees. L4DC (2020)
Jacob H. Seidman, Mahyar Fazlyab, Victor M. Preciado, George J. Pappas
Robust Deep Learning as Optimal Control: Insights and Convergence Guarantees. CoRR (2020)
Jacob H. Seidman, Mahyar Fazlyab, George J. Pappas, Victor M. Preciado
A Chebyshev-Accelerated Primal-Dual Method for Distributed Optimization. CDC (2018)