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Career

· Braumaster, Brauweise und Technik, Doemens2023–2025
· Bachelor of Technology - BTech, Lebensmittelwissenschaft und -technik, 武汉轻工大学2016–2021
· Braumeister, doemens

Publications (22)

Tackling the Curse of Dimensionality with Physics-Informed Neural Networks
Neural Networks · 2023
173
cited
Augmented Physics-Informed Neural Networks (APINNs): A gating network-based soft domain decomposition methodology
Engineering applications of artificial intelligence · 2022
120
cited
Yell At Your Robot: Improving On-the-Fly from Language Corrections
Robotics: Science and Systems · 2024
119
cited
SERL: A Software Suite for Sample-Efficient Robotic Reinforcement Learning
IEEE International Conference on Robotics and Automation · 2024
100
cited
Hutchinson Trace Estimation for High-Dimensional and High-Order Physics-Informed Neural Networks
Computer Methods in Applied Mechanics and Engineering · 2023
38
cited
Dexterous Manipulation from Images: Autonomous Real-World RL via Substep Guidance
IEEE International Conference on Robotics and Automation · 2022
30
cited
State-space models are accurate and efficient neural operators for dynamical systems
Neural Networks · 2024
27
cited
Score-Based Physics-Informed Neural Networks for High-Dimensional Fokker-Planck Equations
arXiv.org · 2024
22
cited
Bias-Variance Trade-off in Physics-Informed Neural Networks with Randomized Smoothing for High-Dimensional PDEs
SIAM Journal on Scientific Computing · 2023
17
cited
Stochastic Taylor Derivative Estimator: Efficient amortization for arbitrary differential operators
Neural Information Processing Systems · 2024
17
cited
Tensor neural networks for high-dimensional Fokker-Planck equations
Neural Networks · 2024
17
cited
REBOOT: Reuse Data for Bootstrapping Efficient Real-World Dexterous Manipulation
Conference on Robot Learning · 2023
13
cited
D4FT: A Deep Learning Approach to Kohn-Sham Density Functional Theory
International Conference on Learning Representations · 2023
12
cited
Tackling the Curse of Dimensionality in Fractional and Tempered Fractional PDEs with Physics-Informed Neural Networks
Computer Methods in Applied Mechanics and Engineering · 2024
8
cited
TNT: Vision Transformer for Turbulence Simulations
2022
7
cited
DeepOMamba: State-space model for spatio-temporal PDE neural operator learning
Journal of Computational Physics · 2025
6
cited
Score-fPINN: Fractional Score-Based Physics-Informed Neural Networks for High-Dimensional Fokker-Planck-Levy Equations
arXiv.org · 2024
2
cited
Improving Radiomics Reproducibility Using MR Fingerprinting and Physics-Informed Quantization
ISMRM Annual Meeting
Intelligent Safety Monitoring and Early Warning System for Construction Site
World Symposium on Software Engineering · 2020
Weld Gun Spatial Tracking System
2019
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Zheyuan Hu | Researcher Profile | Sotabase | Sotabase