Guangru Li

Guangru Li

Cambridge, UC, PKU
在 cam.ac.uk 的电子邮件经过验证
被引用次数：3556
optoelectronics materials fabrication physics informed ML reliability
Jingfan Wang, Ph.D.

Jingfan Wang, Ph.D.

Lead Project Manager@Flexiv Robotics | Stanford PhD
在 stanford.edu 的电子邮件经过验证
被引用次数：1812
AI for Climate Change Greenhouse Gas Mitigation Life Cycle Analysis Physics-informed ML
Sam Siewert

Sam Siewert

Associate Professor, Computer Science, California State University
在 csuchico.edu 的电子邮件经过验证
被引用次数：1003
Sensor Fusion Real-Time Systems Physics Informed ML High Performance Computing
Mathematics for Artificial Reasoning in Science (MARS) Initiative

Mathematics for Artificial Reasoning in Science (MARS) Initiative

Pacific Northwest National Laboratory
在 pnnl.gov 的电子邮件经过验证
被引用次数：822
Explainable AI Robust AI Physics-informed ML AI Assurance Human Machine Teaming
Smita Chakraborty

Smita Chakraborty

Researcher at Research Institutes of Sweden RISE
在 ri.se 的电子邮件经过验证
被引用次数：701
Physics-informed ML ML in Physics Quantum ML Theoretical Physics Particle Physics
Zeqing Jin

Zeqing Jin

University of California, Berkeley
在 berkeley.edu 的电子邮件经过验证
被引用次数：696
AI-driven and differential design optimization physics-informed ML additive manufacturing
Ben Moseley

Ben Moseley

ETH Zurich AI Center
在 ai.ethz.ch 的电子邮件经过验证
被引用次数：657
Scientific machine learning physics-informed ML differential equations geophysics space
Liqian Peng

Liqian Peng

Google
在 google.com 的电子邮件经过验证
被引用次数：519
In-Context Learning Physics-Informed ML Model Reduction
Saakaar Bhatnagar

Saakaar Bhatnagar

Graduate Student, Stanford University
在 stanford.edu 的电子邮件经过验证
被引用次数：517
Physics Informed ML Deep Learning Mechanics
Wei Zhang

Wei Zhang

University of Alberta, Department of Physics,
在 ualberta.ca 的电子邮件经过验证
被引用次数：454
Seismic imaging Seimsic Inversion least-squares migration Physics-informed ML Wave
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