Zongren Zou - RankMe

26 papers Journal 25Unranked 1

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	Bilevel optimization for learning hyperparameters: Application to solving PDEs and inverse problems with Gaussian processes. CoRR Nicholas H. Nelsen, Houman Owhadi, Andrew M. Stuart, Xianjin Yang, Zongren Zou
2025	J	`jnl`	Learning and discovering multiple solutions using physics-informed neural networks with random initialization and deep ensemble. CoRR Zongren Zou, Zhicheng Wang, George Em Karniadakis
2025	J	`jnl`	Multi-head physics-informed neural networks for learning functional priors and uncertainty quantification. J. Comput. Phys. Zongren Zou, George Em Karniadakis
2024	J	`jnl`	A comprehensive and FAIR comparison between MLP and KAN representations for differential equations and operator networks. CoRR Khemraj Shukla, Juan Diego Toscano, Zhicheng Wang, Zongren Zou, George Em Karniadakis
2024	J	`jnl`	Correcting model misspecification in physics-informed neural networks (PINNs). J. Comput. Phys. Zongren Zou, Xuhui Meng, George Em Karniadakis
2024	J	`jnl`	From PINNs to PIKANs: Recent Advances in Physics-Informed Machine Learning. CoRR Juan Diego Toscano, Vivek Oommen, Alan John Varghese, Zongren Zou, Nazanin Ahmadi Daryakenari, Chenxi Wu, George Em Karniadakis
2024	J	`jnl`	HJ-sampler: A Bayesian sampler for inverse problems of a stochastic process by leveraging Hamilton-Jacobi PDEs and score-based generative models. CoRR Tingwei Meng, Zongren Zou, Jérôme Darbon, George Em Karniadakis
2024	J	`jnl`	Large scale scattering using fast solvers based on neural operators. CoRR Zongren Zou, Adar Kahana, Enrui Zhang, Eli Turkel, Rishikesh Ranade, Jay Pathak, George Em Karniadakis
2024	—	`conf`	Leveraging Hamilton-Jacobi PDEs with time-dependent Hamiltonians for continual scientific machine learning. L4DC Paula X. Chen, Tingwei Meng, Zongren Zou, Jérôme Darbon, George Em Karniadakis
2024	J	`jnl`	Leveraging Multitime Hamilton-Jacobi PDEs for Certain Scientific Machine Learning Problems. SIAM J. Sci. Comput. Paula X. Chen, Tingwei Meng, Zongren Zou, Jérôme Darbon, George Em Karniadakis
2024	J	`jnl`	Leveraging Viscous Hamilton-Jacobi PDEs for Uncertainty Quantification in Scientific Machine Learning. SIAM/ASA J. Uncertain. Quantification Zongren Zou, Tingwei Meng, Paula X. Chen, Jérôme Darbon, George Em Karniadakis
2024	J	`jnl`	Leveraging viscous Hamilton-Jacobi PDEs for uncertainty quantification in scientific machine learning. CoRR Zongren Zou, Tingwei Meng, Paula X. Chen, Jérôme Darbon, George Em Karniadakis
2024	J	`jnl`	NeuralUQ: A Comprehensive Library for Uncertainty Quantification in Neural Differential Equations and Operators. SIAM Rev. Zongren Zou, Xuhui Meng, Apostolos F. Psaros, George E. Karniadakis
2024	J	`jnl`	NeuroSEM: A hybrid framework for simulating multiphysics problems by coupling PINNs and spectral elements. CoRR Khemraj Shukla, Zongren Zou, Chi Hin Chan, Additi Pandey, Zhicheng Wang, George Em Karniadakis
2024	J	`jnl`	Quantification of total uncertainty in the physics-informed reconstruction of CVSim-6 physiology. CoRR Mario De Florio, Zongren Zou, Daniele E. Schiavazzi, George Em Karniadakis
2023	J	`jnl`	A Generative Modeling Framework for Inferring Families of Biomechanical Constitutive Laws in Data-Sparse Regimes. CoRR Minglang Yin, Zongren Zou, Enrui Zhang, Cristina Cavinato, Jay D. Humphrey, George Em Karniadakis
2023	J	`jnl`	Correcting model misspecification in physics-informed neural networks (PINNs). CoRR Zongren Zou, Xuhui Meng, George Em Karniadakis
2023	J	`jnl`	Discovering a reaction-diffusion model for Alzheimer's disease by combining PINNs with symbolic regression. CoRR Zhen Zhang, Zongren Zou, Ellen Kuhl, George Em Karniadakis
2023	J	`jnl`	L-HYDRA: Multi-Head Physics-Informed Neural Networks. CoRR Zongren Zou, George Em Karniadakis
2023	J	`jnl`	Leveraging Hamilton-Jacobi PDEs with time-dependent Hamiltonians for continual scientific machine learning. CoRR Paula X. Chen, Tingwei Meng, Zongren Zou, Jérôme Darbon, George Em Karniadakis
2023	J	`jnl`	Leveraging Multi-time Hamilton-Jacobi PDEs for Certain Scientific Machine Learning Problems. CoRR Paula X. Chen, Tingwei Meng, Zongren Zou, Jérôme Darbon, George Em Karniadakis
2023	J	`jnl`	Uncertainty quantification for noisy inputs-outputs in physics-informed neural networks and neural operators. CoRR Zongren Zou, Xuhui Meng, George Em Karniadakis
2023	J	`jnl`	Uncertainty quantification in scientific machine learning: Methods, metrics, and comparisons. J. Comput. Phys. Apostolos F. Psaros, Xuhui Meng, Zongren Zou, Ling Guo, George Em Karniadakis
2022	J	`jnl`	Bayesian Physics-Informed Neural Networks for real-world nonlinear dynamical systems. CoRR Kevin Linka, Amelie Schäfer, Xuhui Meng, Zongren Zou, George Em Karniadakis, Ellen Kuhl
2022	J	`jnl`	NeuralUQ: A comprehensive library for uncertainty quantification in neural differential equations and operators. CoRR Zongren Zou, Xuhui Meng, Apostolos F. Psaros, George Em Karniadakis
2022	J	`jnl`	Uncertainty Quantification in Scientific Machine Learning: Methods, Metrics, and Comparisons. CoRR Apostolos F. Psaros, Xuhui Meng, Zongren Zou, Ling Guo, George Em Karniadakis