Zecheng Zhang

Publication Activity (10 Years)

Years Active: 2019-2024
Publications (10 Years): 53

Top Topics

Inverse Problems

Reinforcement Learning

Stochastic Gradient

Top Venues

J. Comput. Phys.

Comput. Electron. Agric.

Appl. Math. Comput.

Publications

Christian Moya, Amirhossein Mollaali, Zecheng Zhang, Lu Lu, Guang Lin
Conformalized-DeepONet: A Distribution-Free Framework for Uncertainty Quantification in Deep Operator Networks. CoRR (2024)
Joshua Robinson, Rishabh Ranjan, Weihua Hu, Kexin Huang, Jiaqi Han, Alejandro Dobles, Matthias Fey, Jan Eric Lenssen, Yiwen Yuan, Zecheng Zhang, Xinwei He, Jure Leskovec
RelBench: A Benchmark for Deep Learning on Relational Databases. CoRR (2024)
Na Ou, Zecheng Zhang, Guang Lin
A replica exchange preconditioned Crank-Nicolson Langevin dynamic MCMC method with multi-variance strategy for Bayesian inverse problems. J. Comput. Phys. 510 (2024)
Tianqi Xu, Linyao Chen, Dai-Jie Wu, Yanjun Chen, Zecheng Zhang, Xiang Yao, Zhiqiang Xie, Yongchao Chen, Shilong Liu, Bochen Qian, Philip Torr, Bernard Ghanem, Guohao Li
CRAB: Cross-environment Agent Benchmark for Multimodal Language Model Agents. CoRR (2024)
Zecheng Zhang
MODNO: Multi Operator Learning With Distributed Neural Operators. CoRR (2024)
Jingmin Sun, Yuxuan Liu, Zecheng Zhang, Hayden Schaeffer
Towards a Foundation Model for Partial Differential Equations: Multi-Operator Learning and Extrapolation. CoRR (2024)
Cangqing Wang, Mingxiu Sui, Dan Sun, Zecheng Zhang, Yan Zhou
Theoretical Analysis of Meta Reinforcement Learning: Generalization Bounds and Convergence Guarantees. CoRR (2024)
Shiwei Zhou, Yangzhong Wu, Chu Wang, Huayu Lu, Zecheng Zhang, Zijin Liu, Yongdeng Lei, Fu Chen
Projection of future drought impacts on millet yield in northern Shanxi of China using ensemble machine learning approach. Comput. Electron. Agric. 218 (2024)
Xirui Peng, Qiming Xu, Zheng Feng, Haopeng Zhao, Lianghao Tan, Yan Zhou, Zecheng Zhang, Chenwei Gong, Yingqiao Zheng
Automatic News Generation and Fact-Checking System Based on Language Processing. CoRR (2024)
Weihua Hu, Yiwen Yuan, Zecheng Zhang, Akihiro Nitta, Kaidi Cao, Vid Kocijan, Jure Leskovec, Matthias Fey
PyTorch Frame: A Modular Framework for Multi-Modal Tabular Learning. CoRR (2024)
Qianhui Wan, Zecheng Zhang, Liheng Jiang, Zhaoqi Wang, Yan Zhou
Image anomaly detection and prediction scheme based on SSA optimized ResNet50-BiGRU model. CoRR (2024)
Bowen Song, Soo Min Kwon, Zecheng Zhang, Xinyu Hu, Qing Qu, Liyue Shen
Solving Inverse Problems with Latent Diffusion Models via Hard Data Consistency. ICLR (2024)
Guang Lin, Na Ou, Zecheng Zhang, Zhidong Zhang
Restoring the Discontinuous Heat Equation Source Using Sparse Boundary Data and Dynamic Sensors. CoRR (2023)
Guang Lin, Christian Moya, Zecheng Zhang
B-DeepONet: An enhanced Bayesian DeepONet for solving noisy parametric PDEs using accelerated replica exchange SGLD. J. Comput. Phys. 473 (2023)
Bowen Song, Soo Min Kwon, Zecheng Zhang, Xinyu Hu, Qing Qu, Liyue Shen
Solving Inverse Problems with Latent Diffusion Models via Hard Data Consistency. CoRR (2023)
Zecheng Zhang, Xianfeng Han, Guoqian Xiao
IFA-Net: Isomerous Feature-aware Network for Single-view 3D Reconstruction. IJCNN (2023)
Guanxun Li, Guang Lin, Zecheng Zhang, Quan Zhou
Fast Replica Exchange Stochastic Gradient Langevin Dynamics. CoRR (2023)
Zecheng Zhang, Wing Tat Leung, Hayden Schaeffer
A discretization-invariant extension and analysis of some deep operator networks. CoRR (2023)
Zecheng Zhang, Christian Moya, Wing Tat Leung, Guang Lin, Hayden Schaeffer
Bayesian deep operator learning for homogenized to fine-scale maps for multiscale PDE. CoRR (2023)
Guang Lin, Christian Moya, Zecheng Zhang
Learning the dynamical response of nonlinear non-autonomous dynamical systems with deep operator neural networks. Eng. Appl. Artif. Intell. 125 (2023)
Lu Peng, Zecheng Zhang, Xianyi Wang, Weiyi Qiu, Liqian Zhou, Hui Xiao, Chunxiuzi Liu, Shaohua Tang, Zhiwei Qin, Jiakun Jiang, Zengru Di, Yu Liu
Theoretical perspective on synthetic man-made life: Learning from the origin of life. Quant. Biol. 11 (4) (2023)
Yuxuan Liu, Zecheng Zhang, Hayden Schaeffer
PROSE: Predicting Operators and Symbolic Expressions using Multimodal Transformers. CoRR (2023)
Eric T. Chung, Wing Tat Leung, Sai-Mang Pun, Zecheng Zhang
Multi-agent Reinforcement Learning Aided Sampling Algorithms for a Class of Multiscale Inverse Problems. J. Sci. Comput. 96 (2) (2023)
Yalchin Efendiev, Wing Tat Leung, Wenyuan Li, Zecheng Zhang
Hybrid explicit-implicit learning for multiscale problems with time dependent source. Commun. Nonlinear Sci. Numer. Simul. 120 (2023)
Zecheng Zhang, Christian Moya, Lu Lu, Guang Lin, Hayden Schaeffer
D2NO: Efficient Handling of Heterogeneous Input Function Spaces with Distributed Deep Neural Operators. CoRR (2023)
Navjot Singh, Zecheng Zhang, Xiaoxiao Wu, Naijing Zhang, Siyuan Zhang, Edgar Solomonik
Distributed-memory tensor completion for generalized loss functions in python using new sparse tensor kernels. J. Parallel Distributed Comput. 169 (2022)
Wing Tat Leung, Guang Lin, Zecheng Zhang
NH-PINN: Neural homogenization-based physics-informed neural network for multiscale problems. J. Comput. Phys. 470 (2022)
Yuxin Xiao, Zecheng Zhang, Yuning Mao, Carl Yang, Jiawei Han
SAIS: Supervising and Augmenting Intermediate Steps for Document-Level Relation Extraction. NAACL-HLT (2022)
Yalchin Efendiev, Wing Tat Leung, Guang Lin, Zecheng Zhang
Efficient hybrid explicit-implicit learning for multiscale problems. J. Comput. Phys. 467 (2022)
Guang Li, Christian Moya, Zecheng Zhang
On Learning the Dynamical Response of Nonlinear Control Systems with Deep Operator Networks. CoRR (2022)
Zecheng Zhang, Wing Tat Leung, Hayden Schaeffer
BelNet: Basis enhanced learning, a mesh-free neural operator. CoRR (2022)
Eric T. Chung, Yalchin Efendiev, Sai-Mang Pun, Zecheng Zhang
Computational multiscale method for parabolic wave approximations in heterogeneous media. Appl. Math. Comput. 425 (2022)
Na Ou, Zecheng Zhang, Guang Lin
A replica exchange preconditioned Crank-Nicolson Langevin dynamic MCMC method for Bayesian inverse problems. CoRR (2022)
Yalchin Efendiev, Wing Tat Leung, Wenyuan Li, Zecheng Zhang
Hybrid explicit-implicit learning for multiscale problems with time dependent source. CoRR (2022)
Guang Lin, Yating Wang, Zecheng Zhang
Multi-variance replica exchange SGMCMC for inverse and forward problems via Bayesian PINN. J. Comput. Phys. 460 (2022)
Yuxin Xiao, Zecheng Zhang, Yuning Mao, Carl Yang, Jiawei Han
SAIS: Supervising and Augmenting Intermediate Steps for Document-Level Relation Extraction. CoRR (2021)
Eric T. Chung, Wing Tat Leung, Sai-Mang Pun, Zecheng Zhang
A multi-stage deep learning based algorithm for multiscale model reduction. J. Comput. Appl. Math. 394 (2021)
Wing Tat Leung, Guang Lin, Zecheng Zhang
NH-PINN: Neural homogenization based physics-informed neural network for multiscale problems. CoRR (2021)
Liu Liu, Tieyong Zeng, Zecheng Zhang
A deep neural network approach on solving the linear transport model under diffusive scaling. CoRR (2021)
Guang Lin, Yating Wang, Zecheng Zhang
Multi-variance replica exchange stochastic gradient MCMC for inverse and forward Bayesian physics-informed neural network. CoRR (2021)
Guang Lin, Christian Moya, Zecheng Zhang
Accelerated replica exchange stochastic gradient Langevin diffusion enhanced Bayesian DeepONet for solving noisy parametric PDEs. CoRR (2021)
Yalchin Efendiev, Wing Tat Leung, Guang Lin, Zecheng Zhang
HEI: hybrid explicit-implicit learning for multiscale problems. CoRR (2021)
Boris Chetverushkin, Eric T. Chung, Yalchin Efendiev, Sai-Mang Pun, Zecheng Zhang
Computational multiscale methods for quasi-gas dynamic equations. J. Comput. Phys. 440 (2021)
Guang Lin, Zecheng Zhang, Zhidong Zhang
Theoretical and numerical studies of inverse source problem for the linear parabolic equation with sparse boundary measurements. CoRR (2021)
Eric T. Chung, Yalchin Efendiev, Sai-Mang Pun, Zecheng Zhang
Computational multiscale methods for parabolic wave approximations in heterogeneous media. CoRR (2021)
Zecheng Zhang, Eric T. Chung, Yalchin Efendiev, Wing Tat Leung
Learning Algorithms for Coarsening Uncertainty Space and Applications to Multiscale Simulations. CoRR (2020)
Eric T. Chung, Wing Tat Leung, Sai-Mang Pun, Zecheng Zhang
A multi-stage deep learning based algorithm for multiscale modelreduction. CoRR (2020)
Huajie Shao, Dachun Sun, Jiahao Wu, Zecheng Zhang, Aston Zhang, Shuochao Yao, Shengzhong Liu, Tianshi Wang, Chao Zhang, Tarek F. Abdelzaher
paper2repo: GitHub Repository Recommendation for Academic Papers. WWW (2020)
Eric T. Chung, Yalchin Efendiev, Wing Tat Leung, Sai-Mang Pun, Zecheng Zhang
Multi-agent Reinforcement Learning Accelerated MCMC on Multiscale Inversion Problem. CoRR (2020)
Boris Chetverushkin, Eric T. Chung, Yalchin Efendiev, Sai-Mang Pun, Zecheng Zhang
Computational multiscale methods for quasi-gas dynamic equations. CoRR (2020)
Huajie Shao, Dachun Sun, Jiahao Wu, Zecheng Zhang, Aston Zhang, Shuochao Yao, Shengzhong Liu, Tianshi Wang, Chao Zhang, Tarek F. Abdelzaher
paper2repo: GitHub Repository Recommendation for Academic Papers. CoRR (2020)
Yuxin Xiao, Zecheng Zhang, Carl Yang, Chengxiang Zhai
Non-local Attention Learning on Large Heterogeneous Information Networks. IEEE BigData (2019)
Zecheng Zhang, Xiaoxiao Wu, Naijing Zhang, Siyuan Zhang, Edgar Solomonik
Enabling Distributed-Memory Tensor Completion in Python using New Sparse Tensor Kernels. CoRR (2019)