Alternatives and similar repositories for RBF-Network

Users that are interested in RBF-Network are comparing it to the libraries listed below

• eugeniashurko / rbfnnpy
  Radial Basis Function Neural Network implementation for Python
  ☆88Updated 5 years ago
• insujeon / rbfn
  Radial Basis Function Network - PyTorch
  ☆47Updated 7 years ago
• PetraVidnerova / rbf_keras
  RBF layer for Keras
  ☆144Updated 2 years ago
• SheffieldML / deepGP
  Deep Gaussian Processes in matlab
  ☆93Updated 3 years ago
• ziyuw / rembo
  Bayesian optimization in high-dimensions via random embedding.
  ☆114Updated 11 years ago
• kamperh / bayes_gmm
  Bayesian Gaussian mixture models in Python.
  ☆63Updated 2 years ago
• maziarraissi / ParametricGP
  Parametric Gaussian Process Regression for Big Data
  ☆45Updated 5 years ago
• tsyet12 / EvoOpt
  Python implementation of state-of-art meta-heuristic and evolutionary optimization algorithms.
  ☆13Updated 2 years ago
• Hvass-Labs / swarmops
  Heuristic Optimization for Python
  ☆72Updated 5 years ago
• zi-w / GP-EST
  Bayesian optimization with the Gaussian process assumption
  ☆30Updated 9 years ago
• ebonilla / mtgp
  Multi-task Gaussian Process
  ☆43Updated 10 years ago
• Hvass-Labs / MetaOps
  Tuning the Parameters of Heuristic Optimizers (Meta-Optimization / Hyper-Parameter Optimization)
  ☆55Updated 6 years ago
• skylergrammer / SimulatedAnnealing
  ☆45Updated 4 years ago
• jmetzen / bayesian_optimization
  Bayesian optimization
  ☆37Updated 5 years ago
• RuiShu / nn-bayesian-optimization
  We use a modified neural network instead of Gaussian process for Bayesian optimization.
  ☆108Updated 8 years ago
• yaringal / HeteroscedasticDropoutUncertainty
  Demos demonstrating the difference between homoscedastic and heteroscedastic regression with dropout uncertainty.
  ☆140Updated 9 years ago
• TENGBINN / Bayes-by-Backprop
  TensorFlow implementation of Bayes-by-Backprop algorithm from "Weight Uncertainty in Neural Networks" paper
  ☆51Updated 6 years ago
• rajathkmp / DCGAN
  Implementation of Deep Convolutional Generative Adversarial Networks on MNIST database in Keras
  ☆38Updated 8 years ago
• dhammack / RBFnet
  RBF Network using Theano, climin, and sklearn.
  ☆23Updated 11 years ago
• titu1994 / keras-minimal-rnn
  Keras implementation of MinimalRNN: Toward More Interpretable and Trainable Recurrent Neural Networks
  ☆17Updated 7 years ago
• lmjohns3 / kohonen
  Kohonen vector quantizers (SOM, NG, GNG)
  ☆71Updated 7 years ago
• ghliu / mean-field-fcdnn
  ☆28Updated 5 years ago
• iaroslav-ai / gan-rl
  Training Reinforcement Learning agent using derivative of Generative Recurrent Neural Network model of environment
  ☆24Updated 8 years ago
• hiroyuki-kasai / RSOpt
  Riemannian stochastic optimization algorithms: Version 1.0.3
  ☆64Updated 2 years ago
• keskarnitish / minSQN
  Optimization using Stochastic quasi-Newton methods
  ☆43Updated 8 years ago
• locuslab / icnn
  Input Convex Neural Networks
  ☆294Updated 6 years ago
• saparina / neural-ode
  Experiments with Neural Ordinary Differential Equations on image and text classification tasks
  ☆31Updated 6 years ago
• wohnjayne / eda-suite
  Research code for using generative neural networks in Estimation of Distribution Algorithms (EDAs)
  ☆15Updated 8 years ago
• mynkpl1998 / Deep-Learning-Optimization-Algorithms
  Visualization of various deep learning optimization algorithms using PyTorch automatic differentiation and optimizers.
  ☆59Updated 7 years ago
• jayhack / LSTMVRAE
  Variational Recurrent Auto-Encoder using LSTM encoder/decoder networks
  ☆55Updated 9 years ago