Zecheng Zhang - RankMe

78 papers A* 4B 1Journal 70Unranked 3

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	DeepONet as a multi-Operator extrapolation model: Distributed pretraining with physics-Informed fine-Tuning. J. Comput. Phys. Zecheng Zhang, Christian Moya, Lu Lu, Guang Lin, Hayden Schaeffer
2026	J	`jnl`	PointLMDA: Local masked reconstruction and structural prediction for self-supervised domain adaptation on 3D point clouds. Inf. Fusion Shuxiang Si, Huang Zhang, Jing Guo, Hao Luo, Xin Ning, Zecheng Zhang, Zaiyang Yu, Ning Mao, Wenjie Yu
2026	J	`jnl`	SEAR: Schema-Based Evaluation and Routing for LLM Gateways. CoRR Zecheng Zhang, Han Zheng, Yue Xu
2025	J	`jnl`	A Deep Learning Framework for Multi-Operator Learning: Architectures and Approximation Theory. CoRR Adrien Weihs, Jingmin Sun, Zecheng Zhang, Hayden Schaeffer
2025	J	`jnl`	A discretization-invariant extension and analysis of some deep operator networks. J. Comput. Appl. Math. Zecheng Zhang, Wing Tat Leung, Hayden Schaeffer
2025	J	`jnl`	AVA: Attentive VLM Agent for Mastering StarCraft II. CoRR Weiyu Ma, Yuqian Fu, Zecheng Zhang, Bernard Ghanem, Guohao Li
2025	J	`jnl`	CCS: Controllable and Constrained Sampling with Diffusion Models via Initial Noise Perturbation. CoRR Bowen Song, Zecheng Zhang, Zhaoxu Luo, Jason Hu, Wei Yuan, Jing Jia, Zhengxu Tang, Guanyang Wang, Liyue Shen
2025	—	`conf`	CRAB: Cross-environment Agent Benchmark for Multimodal Language Model Agents. ACL (Findings) Tianqi Xu, Linyao Chen, Dai-Jie Wu, Yanjun Chen, Zecheng Zhang, Xiang Yao, Zhiqiang Xie, Yongchao Chen, Shilong Liu, Bochen Qian, Anjie Yang, Zhaoxuan Jin, Jianbo Deng, Philip Torr, Bernard Ghanem, Guohao Li
2025	J	`jnl`	Coefficient-to-Basis Network: A Fine-Tunable Operator Learning Framework for Inverse Problems with Adaptive Discretizations and Theoretical Guarantees. CoRR Zecheng Zhang, Hao Liu, Wenjing Liao, Guang Lin
2025	A*	`conf`	ContextGNN: Beyond Two-Tower Recommendation Systems. ICLR Yiwen Yuan, Zecheng Zhang, Xinwei He, Akihiro Nitta, Weihua Hu, Manan Shah, Blaz Stojanovic, Shenyang Huang, Jan Eric Lenssen, Jure Leskovec, Matthias Fey
2025	J	`jnl`	Deep Neural Operator Learning for Probabilistic Models. CoRR Erhan Bayraktar, Qi Feng, Zecheng Zhang, Zhaoyu Zhang
2025	J	`jnl`	Finite Element Representation Network (FERN) for Operator Learning with a Localized Trainable Basis. CoRR Zecheng Zhang, Hao Liu, Guosheng Fu, Hayden Schaeffer, Guang Lin
2025	J	`jnl`	PI-MFM: Physics-informed multimodal foundation model for solving partial differential equations. CoRR Min Zhu, Jingmin Sun, Zecheng Zhang, Hayden Schaeffer, Lu Lu
2025	J	`jnl`	PyG 2.0: Scalable Learning on Real World Graphs. CoRR Matthias Fey, Jinu Sunil, Akihiro Nitta, Rishi Puri, Manan Shah, Blaz Stojanovic, Ramona Bendias, Alexandria Barghi, Vid Kocijan, Zecheng Zhang, Xinwei He, Jan Eric Lenssen, Jure Leskovec
2024	J	`jnl`	A replica exchange preconditioned Crank-Nicolson Langevin dynamic MCMC method with multi-variance strategy for Bayesian inverse problems. J. Comput. Phys. Na Ou, Zecheng Zhang, Guang Lin
2024	J	`jnl`	Automatic News Generation and Fact-Checking System Based on Language Processing. CoRR Xirui Peng, Qiming Xu, Zheng Feng, Haopeng Zhao, Lianghao Tan, Yan Zhou, Zecheng Zhang, Chenwei Gong, Yingqiao Zheng
2024	J	`jnl`	Bayesian Deep Operator Learning for Homogenized to Fine-Scale Maps for Multiscale PDE. Multiscale Model. Simul. Zecheng Zhang, Christian Moya, Wing Tat Leung, Guang Lin, Hayden Schaeffer
2024	J	`jnl`	CRAB: Cross-environment Agent Benchmark for Multimodal Language Model Agents. CoRR 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
2024	J	`jnl`	Conformalized-DeepONet: A Distribution-Free Framework for Uncertainty Quantification in Deep Operator Networks. CoRR Christian Moya, Amirhossein Mollaali, Zecheng Zhang, Lu Lu, Guang Lin
2024	J	`jnl`	ContextGNN: Beyond Two-Tower Recommendation Systems. CoRR Yiwen Yuan, Zecheng Zhang, Xinwei He, Akihiro Nitta, Weihua Hu, Dong Wang, Manan Shah, Shenyang Huang, Blaz Stojanovic, Alan Krumholz, Jan Eric Lenssen, Jure Leskovec, Matthias Fey
2024	J	`jnl`	Deep Analysis of Time Series Data for Smart Grid Startup Strategies: A Transformer-LSTM-PSO Model Approach. CoRR Zecheng Zhang
2024	J	`jnl`	DeepONet as a Multi-Operator Extrapolation Model: Distributed Pretraining with Physics-Informed Fine-Tuning. CoRR Zecheng Zhang, Christian Moya, Lu Lu, Guang Lin, Hayden Schaeffer
2024	J	`jnl`	Enhancing Visual Question Answering through Ranking-Based Hybrid Training and Multimodal Fusion. CoRR Peiyuan Chen, Zecheng Zhang, Yiping Dong, Li Zhou, Han Wang
2024	J	`jnl`	Image anomaly detection and prediction scheme based on SSA optimized ResNet50-BiGRU model. CoRR Qianhui Wan, Zecheng Zhang, Liheng Jiang, Zhaoqi Wang, Yan Zhou
2024	J	`jnl`	LeMON: Learning to Learn Multi-Operator Networks. CoRR Jingmin Sun, Zecheng Zhang, Hayden Schaeffer
2024	J	`jnl`	MODNO: Multi Operator Learning With Distributed Neural Operators. CoRR Zecheng Zhang
2024	J	`jnl`	Neural Scaling Laws of Deep ReLU and Deep Operator Network: A Theoretical Study. CoRR Hao Liu, Zecheng Zhang, Wenjing Liao, Hayden Schaeffer
2024	J	`jnl`	PROSE-FD: A Multimodal PDE Foundation Model for Learning Multiple Operators for Forecasting Fluid Dynamics. CoRR Yuxuan Liu, Jingmin Sun, Xinjie He, Griffin Pinney, Zecheng Zhang, Hayden Schaeffer
2024	J	`jnl`	PROSE: Predicting Multiple Operators and Symbolic Expressions using multimodal transformers. Neural Networks Yuxuan Liu, Zecheng Zhang, Hayden Schaeffer
2024	J	`jnl`	Projection of future drought impacts on millet yield in northern Shanxi of China using ensemble machine learning approach. Comput. Electron. Agric. Shiwei Zhou, Yangzhong Wu, Chu Wang, Huayu Lu, Zecheng Zhang, Zijin Liu, Yongdeng Lei, Fu Chen
2024	J	`jnl`	PyTorch Frame: A Modular Framework for Multi-Modal Tabular Learning. CoRR Weihua Hu, Yiwen Yuan, Zecheng Zhang, Akihiro Nitta, Kaidi Cao, Vid Kocijan, Jure Leskovec, Matthias Fey
2024	A*	`conf`	RelBench: A Benchmark for Deep Learning on Relational Databases. NeurIPS 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
2024	J	`jnl`	RelBench: A Benchmark for Deep Learning on Relational Databases. CoRR 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
2024	A*	`conf`	Solving Inverse Problems with Latent Diffusion Models via Hard Data Consistency. ICLR Bowen Song, Soo Min Kwon, Zecheng Zhang, Xinyu Hu, Qing Qu, Liyue Shen
2024	J	`jnl`	Theoretical Analysis of Meta Reinforcement Learning: Generalization Bounds and Convergence Guarantees. CoRR Cangqing Wang, Mingxiu Sui, Dan Sun, Zecheng Zhang, Yan Zhou
2024	J	`jnl`	Time-Series Forecasting, Knowledge Distillation, and Refinement within a Multimodal PDE Foundation Model. CoRR Derek Jollie, Jingmin Sun, Zecheng Zhang, Hayden Schaeffer
2024	J	`jnl`	Towards a Foundation Model for Partial Differential Equations: Multi-Operator Learning and Extrapolation. CoRR Jingmin Sun, Yuxuan Liu, Zecheng Zhang, Hayden Schaeffer
2023	J	`jnl`	A discretization-invariant extension and analysis of some deep operator networks. CoRR Zecheng Zhang, Wing Tat Leung, Hayden Schaeffer
2023	J	`jnl`	B-DeepONet: An enhanced Bayesian DeepONet for solving noisy parametric PDEs using accelerated replica exchange SGLD. J. Comput. Phys. Guang Lin, Christian Moya, Zecheng Zhang
2023	J	`jnl`	Bayesian deep operator learning for homogenized to fine-scale maps for multiscale PDE. CoRR Zecheng Zhang, Christian Moya, Wing Tat Leung, Guang Lin, Hayden Schaeffer
2023	J	`jnl`	D2NO: Efficient Handling of Heterogeneous Input Function Spaces with Distributed Deep Neural Operators. CoRR Zecheng Zhang, Christian Moya, Lu Lu, Guang Lin, Hayden Schaeffer
2023	J	`jnl`	Fast Replica Exchange Stochastic Gradient Langevin Dynamics. CoRR Guanxun Li, Guang Lin, Zecheng Zhang, Quan Zhou
2023	J	`jnl`	Hybrid explicit-implicit learning for multiscale problems with time dependent source. Commun. Nonlinear Sci. Numer. Simul. Yalchin Efendiev, Wing Tat Leung, Wenyuan Li, Zecheng Zhang
2023	B	`conf`	IFA-Net: Isomerous Feature-aware Network for Single-view 3D Reconstruction. IJCNN Zecheng Zhang, Xianfeng Han, Guoqiang Xiao
2023	J	`jnl`	Learning the dynamical response of nonlinear non-autonomous dynamical systems with deep operator neural networks. Eng. Appl. Artif. Intell. Guang Lin, Christian Moya, Zecheng Zhang
2023	J	`jnl`	Multi-agent Reinforcement Learning Aided Sampling Algorithms for a Class of Multiscale Inverse Problems. J. Sci. Comput. Eric T. Chung, Wing Tat Leung, Sai-Mang Pun, Zecheng Zhang
2023	J	`jnl`	PROSE: Predicting Operators and Symbolic Expressions using Multimodal Transformers. CoRR Yuxuan Liu, Zecheng Zhang, Hayden Schaeffer
2023	J	`jnl`	Restoring the Discontinuous Heat Equation Source Using Sparse Boundary Data and Dynamic Sensors. CoRR Guang Lin, Na Ou, Zecheng Zhang, Zhidong Zhang
2023	J	`jnl`	Solving Inverse Problems with Latent Diffusion Models via Hard Data Consistency. CoRR Bowen Song, Soo Min Kwon, Zecheng Zhang, Xinyu Hu, Qing Qu, Liyue Shen
2023	J	`jnl`	Theoretical perspective on synthetic man-made life: Learning from the origin of life. Quant. Biol. Lu Peng, Zecheng Zhang, Xianyi Wang, Weiyi Qiu, Liqian Zhou, Hui Xiao, Chunxiuzi Liu, Shaohua Tang, Zhiwei Qin, Jiakun Jiang, Zengru Di, Yu Liu
2022	J	`jnl`	A replica exchange preconditioned Crank-Nicolson Langevin dynamic MCMC method for Bayesian inverse problems. CoRR Na Ou, Zecheng Zhang, Guang Lin
2022	J	`jnl`	BelNet: Basis enhanced learning, a mesh-free neural operator. CoRR Zecheng Zhang, Wing Tat Leung, Hayden Schaeffer
2022	J	`jnl`	Computational multiscale method for parabolic wave approximations in heterogeneous media. Appl. Math. Comput. Eric T. Chung, Yalchin Efendiev, Sai-Mang Pun, Zecheng Zhang
2022	J	`jnl`	Distributed-memory tensor completion for generalized loss functions in python using new sparse tensor kernels. J. Parallel Distributed Comput. Navjot Singh, Zecheng Zhang, Xiaoxiao Wu, Naijing Zhang, Siyuan Zhang, Edgar Solomonik
2022	J	`jnl`	Efficient hybrid explicit-implicit learning for multiscale problems. J. Comput. Phys. Yalchin Efendiev, Wing Tat Leung, Guang Lin, Zecheng Zhang
2022	J	`jnl`	Hybrid explicit-implicit learning for multiscale problems with time dependent source. CoRR Yalchin Efendiev, Wing Tat Leung, Wenyuan Li, Zecheng Zhang
2022	J	`jnl`	Multi-variance replica exchange SGMCMC for inverse and forward problems via Bayesian PINN. J. Comput. Phys. Guang Lin, Yating Wang, Zecheng Zhang
2022	J	`jnl`	NH-PINN: Neural homogenization-based physics-informed neural network for multiscale problems. J. Comput. Phys. Wing Tat Leung, Guang Lin, Zecheng Zhang
2022	J	`jnl`	On Learning the Dynamical Response of Nonlinear Control Systems with Deep Operator Networks. CoRR Guang Lin, Christian Moya, Zecheng Zhang
2022	—	`conf`	SAIS: Supervising and Augmenting Intermediate Steps for Document-Level Relation Extraction. NAACL-HLT Yuxin Xiao, Zecheng Zhang, Yuning Mao, Carl Yang, Jiawei Han
2021	J	`jnl`	A deep neural network approach on solving the linear transport model under diffusive scaling. CoRR Liu Liu, Tieyong Zeng, Zecheng Zhang
2021	J	`jnl`	A multi-stage deep learning based algorithm for multiscale model reduction. J. Comput. Appl. Math. Eric T. Chung, Wing Tat Leung, Sai-Mang Pun, Zecheng Zhang
2021	J	`jnl`	Accelerated replica exchange stochastic gradient Langevin diffusion enhanced Bayesian DeepONet for solving noisy parametric PDEs. CoRR Guang Lin, Christian Moya, Zecheng Zhang
2021	J	`jnl`	Computational multiscale methods for parabolic wave approximations in heterogeneous media. CoRR Eric T. Chung, Yalchin Efendiev, Sai-Mang Pun, Zecheng Zhang
2021	J	`jnl`	Computational multiscale methods for quasi-gas dynamic equations. J. Comput. Phys. Boris Chetverushkin, Eric T. Chung, Yalchin Efendiev, Sai-Mang Pun, Zecheng Zhang
2021	J	`jnl`	HEI: hybrid explicit-implicit learning for multiscale problems. CoRR Yalchin Efendiev, Wing Tat Leung, Guang Lin, Zecheng Zhang
2021	J	`jnl`	Multi-variance replica exchange stochastic gradient MCMC for inverse and forward Bayesian physics-informed neural network. CoRR Guang Lin, Yating Wang, Zecheng Zhang
2021	J	`jnl`	NH-PINN: Neural homogenization based physics-informed neural network for multiscale problems. CoRR Wing Tat Leung, Guang Lin, Zecheng Zhang
2021	J	`jnl`	SAIS: Supervising and Augmenting Intermediate Steps for Document-Level Relation Extraction. CoRR Yuxin Xiao, Zecheng Zhang, Yuning Mao, Carl Yang, Jiawei Han
2021	J	`jnl`	Theoretical and numerical studies of inverse source problem for the linear parabolic equation with sparse boundary measurements. CoRR Guang Lin, Zecheng Zhang, Zhidong Zhang
2020	J	`jnl`	A multi-stage deep learning based algorithm for multiscale modelreduction. CoRR Eric T. Chung, Wing Tat Leung, Sai-Mang Pun, Zecheng Zhang
2020	J	`jnl`	Computational multiscale methods for quasi-gas dynamic equations. CoRR Boris Chetverushkin, Eric T. Chung, Yalchin Efendiev, Sai-Mang Pun, Zecheng Zhang
2020	J	`jnl`	Learning Algorithms for Coarsening Uncertainty Space and Applications to Multiscale Simulations. CoRR Zecheng Zhang, Eric T. Chung, Yalchin Efendiev, Wing Tat Leung
2020	J	`jnl`	Multi-agent Reinforcement Learning Accelerated MCMC on Multiscale Inversion Problem. CoRR Eric T. Chung, Yalchin Efendiev, Wing Tat Leung, Sai-Mang Pun, Zecheng Zhang
2020	A*	`conf`	paper2repo: GitHub Repository Recommendation for Academic Papers. WWW Huajie Shao, Dachun Sun, Jiahao Wu, Zecheng Zhang, Aston Zhang, Shuochao Yao, Shengzhong Liu, Tianshi Wang, Chao Zhang, Tarek F. Abdelzaher
2020	J	`jnl`	paper2repo: GitHub Repository Recommendation for Academic Papers. CoRR Huajie Shao, Dachun Sun, Jiahao Wu, Zecheng Zhang, Aston Zhang, Shuochao Yao, Shengzhong Liu, Tianshi Wang, Chao Zhang, Tarek F. Abdelzaher
2019	J	`jnl`	Enabling Distributed-Memory Tensor Completion in Python using New Sparse Tensor Kernels. CoRR Zecheng Zhang, Xiaoxiao Wu, Naijing Zhang, Siyuan Zhang, Edgar Solomonik
2019	—	`conf`	Non-local Attention Learning on Large Heterogeneous Information Networks. IEEE BigData Yuxin Xiao, Zecheng Zhang, Carl Yang, ChengXiang Zhai