Da Long - RankMe

21 papers A* 4A 2Journal 15

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	StFT: Spatio-temporal Fourier Transformer for Long-term Dynamics Prediction. Trans. Mach. Learn. Res. Da Long, Shandian Zhe, Samuel Williams, Leonid Oliker, Zhe Bai
2025	A*	`conf`	Arbitrarily-Conditioned Multi-Functional Diffusion for Multi-Physics Emulation. ICML Da Long, Zhitong Xu, Guang Yang, Akil Narayan, Shandian Zhe
2025	J	`jnl`	Decoupled peak property learning for efficient and interpretable electronic circular dichroism spectrum prediction. Nat. Comput. Sci. Hao Li, Da Long, Li Yuan, Yu Wang, Yonghong Tian, Xinchang Wang, Fanyang Mo
2025	J	`jnl`	Deep Gaussian Processes for Functional Maps. CoRR Matthew Lowery, Zhitong Xu, Da Long, Keyan Chen, Daniel S. Johnson, Yang Bai, Varun Shankar, Shandian Zhe
2025	A	`conf`	Invertible Fourier Neural Operators for Tackling Both Forward and Inverse Problems. AISTATS Da Long, Zhitong Xu, Qiwei Yuan, Yin Yang, Shandian Zhe
2025	J	`jnl`	LightPose: A lightweight fatigue-aware pose estimation framework. J. Ind. Inf. Integr. Da Long, Sheng Yang
2025	J	`jnl`	Pseudo-Physics-Informed Neural Operators: Enhancing Operator Learning from Limited Data. CoRR Keyan Chen, Yile Li, Da Long, Zhitong Xu, Wei Xing, Jacob D. Hochhalter, Shandian Zhe
2025	J	`jnl`	Pseudo-Physics-Informed Neural Operators: Enhancing Operator Learning from Limited Data. Trans. Mach. Learn. Res. Keyan Chen, Yile Li, Da Long, Zhitong Xu, Wei W. Xing, Jacob D. Hochhalter, Shandian Zhe
2025	J	`jnl`	Spatio-temporal Fourier Transformer (StFT) for Long-term Dynamics Prediction. CoRR Da Long, Shandian Zhe, Samuel Williams, Leonid Oliker, Zhe Bai
2025	A*	`conf`	Toward Efficient Kernel-Based Solvers for Nonlinear PDEs. ICML Zhitong Xu, Da Long, Yiming Xu, Guang Yang, Shandian Zhe, Houman Owhadi
2024	J	`jnl`	Arbitrarily-Conditioned Multi-Functional Diffusion for Multi-Physics Emulation. CoRR Da Long, Zhitong Xu, Guang Yang, Akil Narayan, Shandian Zhe
2024	J	`jnl`	Deep peak property learning for efficient chiral molecules ECD spectra prediction. CoRR Hao Li, Da Long, Li Yuan, Yonghong Tian, Xinchang Wang, Fanyang Mo
2024	A	`conf`	Equation Discovery with Bayesian Spike-and-Slab Priors and Efficient Kernels. AISTATS Da Long, Wei W. Xing, Aditi S. Krishnapriyan, Robert M. Kirby, Shandian Zhe, Michael W. Mahoney
2024	J	`jnl`	Invertible Fourier Neural Operators for Tackling Both Forward and Inverse Problems. CoRR Da Long, Shandian Zhe
2024	A*	`conf`	Solving High Frequency and Multi-Scale PDEs with Gaussian Processes. ICLR Shikai Fang, Madison Cooley, Da Long, Shibo Li, Mike Kirby, Shandian Zhe
2024	J	`jnl`	Toward Efficient Kernel-Based Solvers for Nonlinear PDEs. CoRR Zhitong Xu, Da Long, Yiming Xu, Guang Yang, Shandian Zhe, Houman Owhadi
2023	J	`jnl`	Equation Discovery with Bayesian Spike-and-Slab Priors and Efficient Kernels. CoRR Da Long, Wei W. Xing, Aditi S. Krishnapriyan, Robert M. Kirby, Shandian Zhe, Michael W. Mahoney
2023	J	`jnl`	Solving High Frequency and Multi-Scale PDEs with Gaussian Processes. CoRR Shikai Fang, Madison Cooley, Da Long, Shibo Li, Robert M. Kirby, Shandian Zhe
2022	J	`jnl`	A Kernel Approach for PDE Discovery and Operator Learning. CoRR Da Long, Nicole Mrvaljevic, Shandian Zhe, Bamdad Hosseini
2022	A*	`conf`	AutoIP: A United Framework to Integrate Physics into Gaussian Processes. ICML Da Long, Zheng Wang, Aditi S. Krishnapriyan, Robert M. Kirby, Shandian Zhe, Michael W. Mahoney
2022	J	`jnl`	AutoIP: A United Framework to Integrate Physics into Gaussian Processes. CoRR Da Long, Zheng Wang, Aditi S. Krishnapriyan, Robert M. Kirby, Shandian Zhe, Michael W. Mahoney