Description

• TF : Tensorflow
• PT : PyTorch
• SK : Scikit-Learn

Spiking Neural Networks

Title	Description	Framework	Link
BindsNET	spiking neural networks	PT	[Link]
NengoDL	spiking neural networks	TF	[Link]

Meta Learning

Title	Description	Framework	Link
learn2learn	software library for meta-learning research	PT	[Link]

Graph Neural Networks

Title	Description	Framework	Link
Spektral	graph neural networks	TF	[Link]
PyTorch geometric	graph neural networks	PT	[Link]
Deep Graph Library (DGL)	graph neural networks	-	[Link]

Recommend Systems

Title	Description	Framework	Link
tensorflow-recommenders	recommender system models	TF	[Link]

Neural Structured Learning

Title	Description	Framework	Link
neural-structured-learning	leveraging structured signals	TF	[Link]

PyTorch Application

Title	Description	Framework	Link
early-stopping-pytorch	Pytorch early-stopping	PT	[Link]
pytorch-metric-learning	Many loss and utils	PT	[Link]
pytorch-lighting	The lightweight PyTorch wrapper	PT	[Link]

Optimizers

Title	Description	Framework	Link
pytorch-optimizer	Many optimizer	PT	[Link]

Hyperparameter Optimizer

Title	Description	Framework	Link
Bayesian Optimization	Bayesain optimization library	-	[Link]
NiaPy	Nature Inspired Algorithms	-	[Link]
DEAP	Genetic Algorithms library	-	[Link]
Optuna	Random Search, Bayesian Optimization	-	[Link]
Hpbandster	HyperBand and BOHB optimization library	-	[Link]
NNI	Include many optimization library	-	[Link]

Feature Selection

Title	Description	Framework	Link
FeatureSelectionGA	FeatureSelection using Genetic Algorithms	-	[Link]

Automated Learning

Title	Description	Framework	Link
NiaAML	FeatureSelection using AutoML	-	[Link]
PyCaret	low-code machine learning library	SK	[Link]
AutoKeras	An AutoML system based on Keras	TF	[Link]