By training machine learning models with examples of basic science, Miles Cranmer hopes to push the pace of scientific ...

A new Nature Physics study has shed light on the long-hypothesized liquid-liquid critical point where water simultaneously ...

These quantum-inspired tensor networks represent the turbulence probability distributions in a hyper-compressed format, which ...

To estimate these parameters, the team developed a physics-informed neural network (PINN) model—a modified machine learning algorithm that incorporates the rate and state friction law—to ...

This neural network is effective across a variety of physics problems, including heat transfer and fluid flow. It achieves over 96% accuracy in data enhancement while using 42.76% less ...

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