Maruti Kumar Mudunuru's repositories
species_area_scaling
Quantifying Dissolved Organic Matter Scaling Relationships and Trends in Watersheds
AI_ModEx_PFLOTRAN
AI-enabled model-experimental-data integration to emulate and calibrate PFLOTRAN
archived_codes_for_sfa_modeling
repo for setting up all SFA groundwater models before 2019
dl4sci-scaling-tutorial
Deep Learning Scaling tutorial material for the Deep Learning for Science School at Berkeley Lab
dl4sci-tf-tutorials
Official TensorFlow 2.0 tutorial notebooks for the Deep Learning for Science School at LBNL
EOS-ESSI-Data-Table
In this Github link, we provide a table that summarizes FAIR data repositories. This table is for Earth and Space Science Informatics EOS-article.
GeoThermalCloud.jl
Geothermal Cloud for Machine Learning
GPTutorial
A hands-on tutorial on supervised learning with Gaussian processes
LabelFree-DNN-Surrogate
Surrogate Modeling for Fluid Flows Based on Physics-Constrained Label-Free Deep Learning
LipschitzRNN
Lipschitz Recurrent Neural Networks
ML_E3SM_ELM
ML scripts for E3SM-ELM model
neural-networks-and-deep-learning
This is my assignment on Andrew Ng's course “neural networks and deep learning”
PFLOTRAN-SIP
This is a public repository of input files that were used for the example problem of PFLOTRAN-SIP framework.
pinns
Physics-informed neural networks
PINNs-TF2.0
TensorFlow 2.0 implementation of Maziar Raissi's Physics Informed Neural Networks (PINNs).
TensorDiffEq
Efficient and Scalable Physics-Informed Deep Learning and Scientific Machine Learning on top of Tensorflow for multi-worker distributed computing
TensorFlow-Examples
TensorFlow Tutorial and Examples for Beginners (support TF v1 & v2)
testing_data
test some data and read it to Google Colab
training-data-analyst
Labs and demos for courses for GCP Training (http://cloud.google.com/training).
TRIPODS_Winter_School_2022
Practicum on Supervised Learning in Function Spaces
Understanding-NN
Tensorflow tutorial for various Deep Neural Network visualization techniques
XCT_toy_data
Simple XCT toy data analysis