Computational-Physics-and-Machine-Learning-Reading-List

A list of papers relating Computational Physics and Machine Learning. This list is by no means complete so if there are other resources that you feel are missing either send me a link to [email protected] or do a pull request. I will try to add to this list as much as possible.

Computational Fluid Dynamics

Papers

Accelerating Eulerian Fluid Simulation With Convolutional Networks ( Paper Notes )

Lat-Net: Compressing Lattice Boltzmann Flow Simulations using Deep Neural Networks ( Paper Notes )

Convolutional Neural Networks for Steady Flow Approximation ( Paper Notes )

Data-driven projection method in fluid simulation

Deep Learning for Flow Sculpting: Insights into Efficient Learning using Scientific Simulation Data ( Paper Notes )

Deep Learning Fluid Mechanics

Deep Learning in Fluid Mechanics

Reynolds averaged turbulence modelling using deep neural networks with embedded invariance

Deep Learning the Physics of Transport Phenomena

A unified deep artificial neural network approach to partial differential equations in complex geometries

Solving parametric PDE problems with artificial neural networks

Online Discussions

Using CNNs for fluid flow analysis

CFD + Machine learning for super fast simulations

Use of machine learning in computational fluid dynamics

Quantum Mechanics

Papers

Deep learning and the Schr¨odinger equation ( Paper Notes )

Nuclear Physics / High Energy Physics

Papers

CaloGAN: Simulating 3D High Energy Particle Showers in Multi-Layer Electromagnetic Calorimeters with Generative Adversarial Networks ( Paper Notes )