Geothermal Cloud for Machine Learning

Efficient and Scalable Physics-Informed Deep Learning and Scientific Machine Learning on top of Tensorflow for multi-worker distributed computing

Practicum on Supervised Learning in Function Spaces

Implementation of the paper "Self-Adaptive Physics-Informed Neural Networks using a Soft Attention Mechanism" [AAAI-MLPS 2021]

codes for PINNs

Physics-informed neural networks

Lipschitz Recurrent Neural Networks

This is my assignment on Andrew Ng's course “neural networks and deep learning”

Labs and demos for courses for GCP Training (http://cloud.google.com/training).

Tensorflow tutorial for various Deep Neural Network visualization techniques

TensorFlow Tutorial and Examples for Beginners (support TF v1 & v2)

Surrogate Modeling for Fluid Flows Based on Physics-Constrained Label-Free Deep Learning

A hands-on tutorial on supervised learning with Gaussian processes

TensorFlow 2.0 implementation of Maziar Raissi's Physics Informed Neural Networks (PINNs).

repo for setting up all SFA groundwater models before 2019

Deep Learning Scaling tutorial material for the Deep Learning for Science School at Berkeley Lab

This is a public repository of input files that were used for the example problem of PFLOTRAN-SIP framework.

Official TensorFlow 2.0 tutorial notebooks for the Deep Learning for Science School at LBNL