Zecheng Zhang
Orcid: 0000-0001-9240-1829
According to our database1,
Zecheng Zhang
authored at least 47 papers
between 2019 and 2024.
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Bibliography
2024
A replica exchange preconditioned Crank-Nicolson Langevin dynamic MCMC method with multi-variance strategy for Bayesian inverse problems.
J. Comput. Phys., 2024
CoRR, 2024
Image anomaly detection and prediction scheme based on SSA optimized ResNet50-BiGRU model.
CoRR, 2024
Theoretical Analysis of Meta Reinforcement Learning: Generalization Bounds and Convergence Guarantees.
CoRR, 2024
CoRR, 2024
Towards a Foundation Model for Partial Differential Equations: Multi-Operator Learning and Extrapolation.
CoRR, 2024
Conformalized-DeepONet: A Distribution-Free Framework for Uncertainty Quantification in Deep Operator Networks.
CoRR, 2024
Projection of future drought impacts on millet yield in northern Shanxi of China using ensemble machine learning approach.
Comput. Electron. Agric., 2024
Proceedings of the Twelfth International Conference on Learning Representations, 2024
2023
Theoretical perspective on synthetic man-made life: Learning from the origin of life.
Quant. Biol., December, 2023
Multi-agent Reinforcement Learning Aided Sampling Algorithms for a Class of Multiscale Inverse Problems.
J. Sci. Comput., August, 2023
Hybrid explicit-implicit learning for multiscale problems with time dependent source.
Commun. Nonlinear Sci. Numer. Simul., June, 2023
B-DeepONet: An enhanced Bayesian DeepONet for solving noisy parametric PDEs using accelerated replica exchange SGLD.
J. Comput. Phys., 2023
Learning the dynamical response of nonlinear non-autonomous dynamical systems with deep operator neural networks.
Eng. Appl. Artif. Intell., 2023
D2NO: Efficient Handling of Heterogeneous Input Function Spaces with Distributed Deep Neural Operators.
CoRR, 2023
Restoring the Discontinuous Heat Equation Source Using Sparse Boundary Data and Dynamic Sensors.
CoRR, 2023
CoRR, 2023
Bayesian deep operator learning for homogenized to fine-scale maps for multiscale PDE.
CoRR, 2023
CoRR, 2023
Proceedings of the International Joint Conference on Neural Networks, 2023
2022
Distributed-memory tensor completion for generalized loss functions in python using new sparse tensor kernels.
J. Parallel Distributed Comput., 2022
Multi-variance replica exchange SGMCMC for inverse and forward problems via Bayesian PINN.
J. Comput. Phys., 2022
NH-PINN: Neural homogenization-based physics-informed neural network for multiscale problems.
J. Comput. Phys., 2022
J. Comput. Phys., 2022
A replica exchange preconditioned Crank-Nicolson Langevin dynamic MCMC method for Bayesian inverse problems.
CoRR, 2022
On Learning the Dynamical Response of Nonlinear Control Systems with Deep Operator Networks.
CoRR, 2022
Computational multiscale method for parabolic wave approximations in heterogeneous media.
Appl. Math. Comput., 2022
SAIS: Supervising and Augmenting Intermediate Steps for Document-Level Relation Extraction.
Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2022
2021
J. Comput. Phys., 2021
J. Comput. Appl. Math., 2021
Accelerated replica exchange stochastic gradient Langevin diffusion enhanced Bayesian DeepONet for solving noisy parametric PDEs.
CoRR, 2021
Theoretical and numerical studies of inverse source problem for the linear parabolic equation with sparse boundary measurements.
CoRR, 2021
Multi-variance replica exchange stochastic gradient MCMC for inverse and forward Bayesian physics-informed neural network.
CoRR, 2021
Computational multiscale methods for parabolic wave approximations in heterogeneous media.
CoRR, 2021
A deep neural network approach on solving the linear transport model under diffusive scaling.
CoRR, 2021
2020
CoRR, 2020
CoRR, 2020
Learning Algorithms for Coarsening Uncertainty Space and Applications to Multiscale Simulations.
CoRR, 2020
Proceedings of the WWW '20: The Web Conference 2020, Taipei, Taiwan, April 20-24, 2020, 2020
2019
Enabling Distributed-Memory Tensor Completion in Python using New Sparse Tensor Kernels.
CoRR, 2019
Proceedings of the 2019 IEEE International Conference on Big Data (IEEE BigData), 2019