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Name: Maruti Kumar Mudunuru
Type: User
Company: Pacific Northwest National Laboratory (PNNL))
Bio: I am Staff Scientist at PNNL working on coupling process models with data using AI/ML.
Location: Richland, WA, USA
Name: Maruti Kumar Mudunuru
Type: User
Company: Pacific Northwest National Laboratory (PNNL))
Bio: I am Staff Scientist at PNNL working on coupling process models with data using AI/ML.
Location: Richland, WA, USA
AI-enabled model-experimental-data integration to emulate and calibrate PFLOTRAN
repo for setting up all SFA groundwater models before 2019
Bayesian deep convolutional encoder-decoder networks for surrogate modeling and uncertainty quantification
Deep Learning to Estimate Permeability using Geophysical Data
Deep Learning Scaling tutorial material for the Deep Learning for Science School at Berkeley Lab
Official TensorFlow 2.0 tutorial notebooks for the Deep Learning for Science School at LBNL
Scalable deep learning for SWAT model calibration
In this Github link, we provide a table that summarizes FAIR data repositories. This table is for Earth and Space Science Informatics EOS-article.
Geothermal Cloud for Machine Learning
A hands-on tutorial on supervised learning with Gaussian processes
:orange_book: HOTTBOX: Higher Order Tensors ToolBOX. Tutorials
Surrogate Modeling for Fluid Flows Based on Physics-Constrained Label-Free Deep Learning
Lipschitz Recurrent Neural Networks
ML scripts for E3SM-ELM model
This is my assignment on Andrew Ng's course “neural networks and deep learning”
This is a public repository of input files that were used for the example problem of PFLOTRAN-SIP framework.
codes for PINNs
Physics-informed neural networks
TensorFlow 2.0 implementation of Maziar Raissi's Physics Informed Neural Networks (PINNs).
Implementation of the paper "Self-Adaptive Physics-Informed Neural Networks using a Soft Attention Mechanism" [AAAI-MLPS 2021]
Tutorial on seismic signal/noise classification; from linear to deep classifiers
Quantifying Dissolved Organic Matter Scaling Relationships and Trends in Watersheds
Efficient and Scalable Physics-Informed Deep Learning and Scientific Machine Learning on top of Tensorflow for multi-worker distributed computing
TensorFlow Tutorial and Examples for Beginners (support TF v1 & v2)
Layerwise Relevance Propagation with Deep Taylor Series in TensorFlow
A declarative, efficient, and flexible JavaScript library for building user interfaces.
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
An Open Source Machine Learning Framework for Everyone
The Web framework for perfectionists with deadlines.
A PHP framework for web artisans
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
Some thing interesting about web. New door for the world.
A server is a program made to process requests and deliver data to clients.
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
Some thing interesting about visualization, use data art
Some thing interesting about game, make everyone happy.
We are working to build community through open source technology. NB: members must have two-factor auth.
Open source projects and samples from Microsoft.
Google ❤️ Open Source for everyone.
Alibaba Open Source for everyone
Data-Driven Documents codes.
China tencent open source team.