Alternatives and similar repositories for GAKeras

Users that are interested in GAKeras are comparing it to the libraries listed below

• shibuiwilliam / keras_gpyopt
  Using Bayesian Optimization to optimize hyper parameter in Keras-made neural network model.
  ☆57Updated 7 years ago
• maxim5 / hyper-engine
  Python library for Bayesian hyper-parameters optimization
  ☆91Updated 7 years ago
• aqibsaeed / Genetic-Algorithm-RNN
  Using Genetic Algorithms to optimize Recurrent Neural Network's Configuration
  ☆81Updated 8 years ago
• sorend / fylearn
  Fuzzy machine learning algorithms implementing the scikit-learn interface.
  ☆78Updated 2 weeks ago
• floydhub / hyperparameters-search-examples
  Code examples for https://blog.floydhub.com/guide-to-hyperparameters-search-for-deep-learning-models/
  ☆11Updated 6 years ago
• cc-skuehn / Manifold_Learning
  Worked examples about manifold learning using sklearn and jupyter
  ☆51Updated 7 years ago
• yuqirose / tensor_train_RNN
  Clean repo for tensor-train RNN implemented in TensorFlow
  ☆69Updated 6 years ago
• baptistar / BOCS
  Bayesian Optimization of Combinatorial Structures
  ☆102Updated 6 years ago
• lawrennd / old_talks
  Talks from Neil Lawrence
  ☆54Updated 2 years ago
• thuijskens / bayesian-optimization
  Python code for bayesian optimization using Gaussian processes
  ☆314Updated 9 years ago
• zhulingchen / tfp-tutorial
  TensorFlow Probability Tutorial
  ☆38Updated 6 years ago
• pablormier / yabox
  Yet another black-box optimization library for Python
  ☆138Updated 3 years ago
• ngorbach / Variational_Gradient_Matching_for_Dynamical_Systems
  Sample code for the NIPS paper "Scalable Variational Inference for Dynamical Systems"
  ☆27Updated 6 years ago
• SheffieldML / PyDeepGP
  Deep Gaussian Processes in Python
  ☆236Updated 4 years ago
• shz9 / csc2541-ml-project
  Modeling Uncertainty in RNNs for Time Series Forecasting
  ☆15Updated 8 years ago
• Jianbo-Lab / CCM
  ☆74Updated 7 years ago
• maziarraissi / ParametricGP
  Parametric Gaussian Process Regression for Big Data
  ☆45Updated 5 years ago
• gmontamat / gentun
  Hyperparameter tuning for machine learning models using a distributed genetic algorithm
  ☆91Updated last year
• zjost / bayesian-linear-regression
  A python tutorial for a Bayesian treatment of Linear Regression: https://zjost.github.io/bayesian-linear-regression/
  ☆83Updated 9 years ago
• abhinavralhan / kohonen-maps
  Implementation of SOM and GSOM
  ☆73Updated 2 weeks ago
• cangermueller / ppca
  Probabilistic Principal Component Analysis
  ☆64Updated 8 years ago
• jjfeng / spinn
  Sparse-input neural networks
  ☆23Updated 2 years ago
• weichin11 / Keras_ODENet
  Implementation of (2018) Neural Ordinary Differential Equations on Keras
  ☆66Updated 6 years ago
• twhughes / Symbolic-Regression
  predicting equations from raw data with deep learning
  ☆57Updated 7 years ago
• acba / elm
  Python Extreme Learning Machine (ELM) is a machine learning technique used for classification/regression tasks.
  ☆94Updated 4 years ago
• kumar-shridhar / Master-Thesis-BayesianCNN
  Master Thesis on Bayesian Convolutional Neural Network using Variational Inference
  ☆264Updated 6 years ago
• clinicalml / dmm
  Deep Markov Models
  ☆132Updated 6 years ago
• shibuiwilliam / Keras_Autoencoder
  Autoencoders using Keras
  ☆77Updated 8 years ago
• wujian16 / Cornell-MOE
  A Python library for the state-of-the-art Bayesian optimization algorithms, with the core implemented in C++.
  ☆273Updated 5 years ago
• msmbuilder / vde
  Variational Autoencoder for Dimensionality Reduction of Time-Series
  ☆189Updated 3 years ago