Alternatives and similar repositories for rbfn

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

• hutec / UncertaintyNN
  Implementation and evaluation of different approaches to get uncertainty in neural networks
  ☆140Updated 7 years ago
• maka89 / Deep-Kernel-GP
  Deep Kernel Learning. Gaussian Process Regression where the input is a neural network mapping of x that maximizes the marginal likelihood
  ☆93Updated 7 years ago
• raj-shah / BayesianCNN
  Bayesian Convolutional Neural Networks with Bernoulli Approximate Variational Inference, Gal et al. 2015
  ☆36Updated 7 years ago
• Riashat / Deep-Bayesian-Active-Learning
  Code for Deep Bayesian Active Learning (ICML 2017)
  ☆112Updated 7 years ago
• Rachnog / disentanglment
  Experiments with beta-VAE to learn disentangled representations from the data
  ☆65Updated 6 years ago
• vincentherrmann / wasserstein-notebook
  Wasserstein / earth mover's distance visualizations
  ☆66Updated 8 years ago
• timudk / SPDENN
  A Discussion on Solving Partial Differential Equations using Neural Networks
  ☆66Updated 6 years ago
• skolouri / swgmm
  Sliced Wasserstein Distance for Learning Gaussian Mixture Models
  ☆66Updated 2 years ago
• geniki / neural-processes
  PyTorch implementation of Neural Processes
  ☆89Updated 6 years ago
• google / wasserstein-dist
  tensorflow implementation of the Wasserstein (aka optimal transport) distance
  ☆72Updated 4 years ago
• hav4ik / Hydra
  Multi-Task Learning Framework on PyTorch. State-of-the-art methods are implemented to effectively train models on multiple tasks.
  ☆149Updated 6 years ago
• wmingwei / restricted-boltzmann-machine-deep-belief-network-deep-boltzmann-machine-in-pytorch
  ☆52Updated 7 years ago
• oarriaga / RBF-Network
  Minimal implementation of a radial basis function network.
  ☆74Updated 6 years ago
• vvanirudh / deep-ensembles-uncertainty
  My implementation of the paper "Simple and Scalable Predictive Uncertainty estimation using Deep Ensembles"
  ☆138Updated 7 years ago
• GabrielBianconi / pytorch-rbm
  Restricted Boltzmann Machines (RBMs) in PyTorch
  ☆162Updated 7 years ago
• vodp / py-kmm
  A Python implementation of Kernel Mean Matching data reweighting algorithm
  ☆33Updated 9 years ago
• kekeblom / DeepCGP
  Deep convolutional gaussian processes.
  ☆80Updated 5 years ago
• kumar-shridhar / Master-Thesis-BayesianCNN
  Master Thesis on Bayesian Convolutional Neural Network using Variational Inference
  ☆264Updated 6 years ago
• mcgrady20150318 / BayesianNeuralNetwork
  a repo sharing Bayesian Neural Network recent papers
  ☆216Updated 6 years ago
• thuml / MTlearn
  Code release for "Learning Multiple Tasks with Multilinear Relationship Networks" (NIPS 2017)
  ☆71Updated 7 years ago
• shuangxu96 / IntroVB
  An introduction to variational Bayesian
  ☆24Updated 6 years ago
• henryre / pytorch-fitmodule
  Super simple fit method for PyTorch Modules
  ☆101Updated 5 years ago
• akosiorek / stacked_capsule_autoencoders
  ☆81Updated 3 years ago
• ZichaoLong / PDE-Net
  PDE-Net: Learning PDEs from Data
  ☆317Updated 4 years ago
• DanielTakeshi / MCMC_and_Dynamics
  Practice with MCMC methods and dynamics (Langevin, Hamiltonian, etc.)
  ☆42Updated 5 years ago
• NicolasDurrande / Gaussian-Process-Regression-handout
  ☆40Updated 8 years ago
• SheffieldML / deepGP
  Deep Gaussian Processes in matlab
  ☆93Updated 3 years ago
• Riashat / Active-Learning-Bayesian-Convolutional-Neural-Networks
  Active Learning on Image Data using Bayesian ConvNets
  ☆138Updated 8 years ago
• pochih / MNIST-multitask
  6️⃣6️⃣6️⃣ Reproduce ICLR '18 under-reviewed paper "MULTI-TASK LEARNING ON MNIST IMAGE DATASETS"
  ☆42Updated 7 years ago
• LynnHo / VAE-Tensorflow
  (beta-)VAE Tensorflow
  ☆50Updated 6 years ago