Perdikaris, Paris

15 publications

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

ICLR 2025 Deep Learning Alternatives of the Kolmogorov Superposition Theorem Leonardo Ferreira Guilhoto, Paris Perdikaris

NeurIPS 2025 Gradient Alignment in Physics-Informed Neural Networks: A Second-Order Optimization Perspective Sifan Wang, Ananyae Kumar Bhartari, Bowen Li, Paris Perdikaris

ICLRW 2024 Ensemble Learning for Physics Informed Neural Networks: A Gradient Boosting Approach Zhiwei Fang, Sifan Wang, Paris Perdikaris

ICLRW 2024 Guided Autoregressive Diffusion Models with Applications to PDE Simulation Federico Bergamin, Cristiana Diaconu, Aliaksandra Shysheya, Paris Perdikaris, José Miguel Hernández-Lobato, Richard E. Turner, Emile Mathieu

NeurIPS 2024 On Conditional Diffusion Models for PDE Simulations Aliaksandra Shysheya, Cristiana Diaconu, Federico Bergamin, Paris Perdikaris, José Miguel Hernández-Lobato, Richard E. Turner, Emile Mathieu

JMLR 2024 PirateNets: Physics-Informed Deep Learning with Residual Adaptive Networks Sifan Wang, Bowen Li, Yuhan Chen, Paris Perdikaris

ICML 2023 Mitigating Propagation Failures in Physics-Informed Neural Networks Using Retain-Resample-Release (r3) Sampling Arka Daw, Jie Bu, Sifan Wang, Paris Perdikaris, Anuj Karpatne

ICMLW 2023 Modeling Accurate Long Rollouts with Temporal Neural PDE Solvers Phillip Lippe, Bastiaan S. Veeling, Paris Perdikaris, Richard E Turner, Johannes Brandstetter

NeurIPS 2023 PDE-Refiner: Achieving Accurate Long Rollouts with Neural PDE Solvers Phillip Lippe, Bas Veeling, Paris Perdikaris, Richard Turner, Johannes Brandstetter

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

JMLR 2022 Learning Operators with Coupled Attention Georgios Kissas, Jacob H. Seidman, Leonardo Ferreira Guilhoto, Victor M. Preciado, George J. Pappas, Paris Perdikaris

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

NeurIPSW 2022 On the Impact of Larger Batch Size in the Training of Physics Informed Neural Networks Shyam Sankaran, Hanwen Wang, Leonardo Ferreira Guilhoto, Paris Perdikaris

NeurIPSW 2021 Enhancing the Trainability and Expressivity of Deep MLPs with Globally Orthogonal Initialization Hanwen Wang, Isabelle Crawford-Eng, Paris Perdikaris