Jacob H. Seidman

17 papers A* 3Journal 11Unranked 3

Year	Rank	Type	Title / Venue / Authors
2025	A*	`conf`	CViT: Continuous Vision Transformer for Operator Learning. ICLR Sifan Wang, Jacob H. Seidman, Shyam Sankaran, Hanwen Wang, George J. Pappas, Paris Perdikaris
2025	J	`jnl`	PolyJuice Makes It Real: Black-Box, Universal Red Teaming for Synthetic Image Detectors. CoRR Sepehr Dehdashtian, Mashrur M. Morshed, Jacob H. Seidman, Gaurav Bharaj, Vishnu Naresh Boddeti
2024	J	`jnl`	Bridging Operator Learning and Conditioned Neural Fields: A Unifying Perspective. CoRR Sifan Wang, Jacob H. Seidman, Shyam Sankaran, Hanwen Wang, George J. Pappas, Paris Perdikaris
2024	J	`jnl`	Score Neural Operator: A Generative Model for Learning and Generalizing Across Multiple Probability Distributions. CoRR Xinyu Liao, Aoyang Qin, Jacob H. Seidman, Junqi Wang, Wei Wang, Paris Perdikaris
2023	J	`jnl`	Gaussian Process Port-Hamiltonian Systems: Bayesian Learning with Physics Prior. CoRR Thomas Beckers, Jacob H. Seidman, Paris Perdikaris, George J. Pappas
2023	A*	`conf`	Variational Autoencoding Neural Operators. ICML Jacob H. Seidman, Georgios Kissas, George J. Pappas, Paris Perdikaris
2023	J	`jnl`	Variational Autoencoding Neural Operators. CoRR Jacob H. Seidman, Georgios Kissas, George J. Pappas, Paris Perdikaris
2022	—	`conf`	Gaussian Process Port-Hamiltonian Systems: Bayesian Learning with Physics Prior. CDC Thomas Beckers, Jacob H. Seidman, Paris Perdikaris, George J. Pappas
2022	J	`jnl`	Learning Operators with Coupled Attention. CoRR Georgios Kissas, Jacob H. Seidman, Leonardo Ferreira Guilhoto, Victor M. Preciado, George J. Pappas, Paris Perdikaris
2022	J	`jnl`	Learning Operators with Coupled Attention. J. Mach. Learn. Res. Georgios Kissas, Jacob H. Seidman, Leonardo Ferreira Guilhoto, Victor M. Preciado, George J. Pappas, Paris Perdikaris
2022	A*	`conf`	NOMAD: Nonlinear Manifold Decoders for Operator Learning. NeurIPS Jacob H. Seidman, Georgios Kissas, Paris Perdikaris, George J. Pappas
2022	J	`jnl`	NOMAD: Nonlinear Manifold Decoders for Operator Learning. CoRR Jacob H. Seidman, Georgios Kissas, Paris Perdikaris, George J. Pappas
2022	J	`jnl`	Random Weight Factorization Improves the Training of Continuous Neural Representations. CoRR Sifan Wang, Hanwen Wang, Jacob H. Seidman, Paris Perdikaris
2020	J	`jnl`	A Control-Theoretic Approach to Analysis and Parameter Selection of Douglas-Rachford Splitting. IEEE Control. Syst. Lett. Jacob H. Seidman, Mahyar Fazlyab, Victor M. Preciado, George J. Pappas
2020	—	`conf`	Robust Deep Learning as Optimal Control: Insights and Convergence Guarantees. L4DC Jacob H. Seidman, Mahyar Fazlyab, Victor M. Preciado, George J. Pappas
2020	J	`jnl`	Robust Deep Learning as Optimal Control: Insights and Convergence Guarantees. CoRR Jacob H. Seidman, Mahyar Fazlyab, Victor M. Preciado, George J. Pappas
2018	—	`conf`	A Chebyshev-Accelerated Primal-Dual Method for Distributed Optimization. CDC Jacob H. Seidman, Mahyar Fazlyab, George J. Pappas, Victor M. Preciado