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genesis

A tool for data center automation

gnip-trend-detection

googlemaps-tsp-ga

Solving the Traveling Salesman Problem using Google Maps and Genetic Algorithms

gpabc.jl

Using Gaussian Processes to subsidise simulations in Approximate Bayesian Computation.

gpinn

gPINN: Gradient-enhanced physics-informed neural networks

gptutorial

A hands-on tutorial on supervised learning with Gaussian processes

gputaskscheduler

GPU Task Scheduler (Python library)

gr-air-modes

Gnuradio Mode-S/ADS-B radio

gr-gsm

Gnuradio blocks and tools for receiving GSM transmissions

gr-id-pinn

Constructing initial data for numerical relativity simulations using physics-informed neural networks.

gradient-centralization

A New Optimization Technique for Deep Neural Networks

gradient-free-optimizers

Simple and reliable optimization with local, global, population-based and sequential techniques in numerical search spaces.

gradientpathologiespinns

gradientweight

gradnorm

graphdmd

Dynamic mode decomposition with dependent structure among observables (Graph DMD)

groundhog

Library for implementing RNNs with Theano

growingneuralgas

Simple implementation of the "growing neural gas" artificial neural network

h2o

h2o = fast statistical, machine learning & math runtime for bigdata

h2o-dev

Fast Scalable Machine Learning API For Smarter Applications

h2o-meetups

h2o-r-notebooks

H2O tutorials as R markdown files

hadoop-auto-install

Auto-Install Hadoop on single node (Standalone machine) or multi node cluster (Multiple machines on same network/Cloud envirnment)

hands-on-meta-learning-with-python

Learning to Learn using One-Shot Learning, MAML, Reptile, Meta-SGD and more with Tensorflow

hardconstraint

Official implementation of *A Unified Hard-Constraint Framework for Solving Geometrically Complex PDEs*

hazelcast-tutorial

Hazelcast Tutorial

hcb-v2

heron

Heron is a surrogate modelling toolkit for python, using Gaussian process regression.

hessian-based-toolbox

The repository accompanying the research paper "Hessian-based toolbox for more reliable and interpretable machines learning physics" by A. Dawid, P. Huembeli, M. Tomza, M. Lewenstein, and A. Dauphin

hibachi

Data simulation software that creates data sets with particular characteristics