Homepage - Zhitong Xu

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Selected Publications (view all )

Arbitrarily-Conditioned Multi-Functional Diffusion for Multi-Physics Emulation

Long Da, Zhitong Xu, Guang Yang, Akil Narayan, Shandian Zhe

Forty-second International Conference on Machine Learning (ICML) 2025

[Paper]

Arbitrarily-Conditioned Multi-Functional Diffusion for Multi-Physics Emulation

Long Da, Zhitong Xu, Guang Yang, Akil Narayan, Shandian Zhe

Forty-second International Conference on Machine Learning (ICML) 2025

[Paper]

Toward Efficient Kernel-Based Solvers for Nonlinear PDEs

Zhitong Xu*, Da Long*, Yiming Xu, Guang Yang, Shandian Zhe, Houman Owhadi (* equal contribution)

Forty-second International Conference on Machine Learning (ICML) 2025

[Paper]

Toward Efficient Kernel-Based Solvers for Nonlinear PDEs

Zhitong Xu*, Da Long*, Yiming Xu, Guang Yang, Shandian Zhe, Houman Owhadi (* equal contribution)

Forty-second International Conference on Machine Learning (ICML) 2025

[Paper]

Standard Gaussian Process is All You Need for High-Dimensional Bayesian Optimization

Zhitong Xu, Haitao Wang, Jeff M. Phillips, Shandian Zhe

The Thirteenth International Conference on Learning Representations (ICLR) 2025 Oral

[Code] [Paper]

Standard Gaussian Process is All You Need for High-Dimensional Bayesian Optimization

Zhitong Xu, Haitao Wang, Jeff M. Phillips, Shandian Zhe

The Thirteenth International Conference on Learning Representations (ICLR) 2025 Oral

[Code] [Paper]

Invertible Fourier Neural Operators for Tackling Both Forward and Inverse Problems

Long Da, Zhitong Xu, Qiwei Yuan, Yin Yang, Shandian Zhe

The 28th International Conference on Artificial Intelligence and Statistics (AISTATS) 2025

[Code] [Paper]

Invertible Fourier Neural Operators for Tackling Both Forward and Inverse Problems

Long Da, Zhitong Xu, Qiwei Yuan, Yin Yang, Shandian Zhe

The 28th International Conference on Artificial Intelligence and Statistics (AISTATS) 2025

[Code] [Paper]

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Selected Publications (view all )

Arbitrarily-Conditioned Multi-Functional Diffusion for Multi-Physics Emulation

Arbitrarily-Conditioned Multi-Functional Diffusion for Multi-Physics Emulation

Toward Efficient Kernel-Based Solvers for Nonlinear PDEs

Toward Efficient Kernel-Based Solvers for Nonlinear PDEs

Standard Gaussian Process is All You Need for High-Dimensional Bayesian Optimization

Standard Gaussian Process is All You Need for High-Dimensional Bayesian Optimization

Invertible Fourier Neural Operators for Tackling Both Forward and Inverse Problems

Invertible Fourier Neural Operators for Tackling Both Forward and Inverse Problems

All publications