Alternatives and similar repositories for PyDeep

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

• BiuBiuBiLL / NPEET_LNC
  local non-uniformity correction for mutual information estimation
  ☆70Updated 3 years ago
• henripal / sgld
  ☆59Updated 6 years ago
• hmorioka / TCL
  Time-Contrastive Learning
  ☆65Updated 6 years ago
• earcher / vilds
  Black box variational inference for state space models
  ☆1Updated 8 years ago
• mattjj / pylds
  some tools for gaussian linear dynamical systems
  ☆89Updated 6 years ago
• sremes / nonstationary-spectral-kernels
  Implementation for Non-stationary Spectral Kernels (NIPS 2017)
  ☆20Updated 5 years ago
• ganguli-lab / deepchaos
  Experiments for the paper "Exponential expressivity in deep neural networks through transient chaos"
  ☆71Updated 8 years ago
• artemyk / nonlinearIB
  Nonlinear Information Bottleneck
  ☆54Updated 2 years ago
• mattjj / pyslds
  ☆95Updated 6 years ago
• hegdepashupati / differential-dgp
  Implementation of stochastic variational inference for differentially deep gaussian processes
  ☆15Updated 6 years ago
• mackelab / delfi
  Density estimation likelihood-free inference. No longer actively developed see https://github.com/mackelab/sbi instead
  ☆73Updated 4 years ago
• wittawatj / fsic-test
  ICML 2017. Kernel-based adaptive linear-time independence test.
  ☆16Updated 3 years ago
• blei-lab / variational-smc
  Reference implementation of variational sequential Monte Carlo proposed by Naesseth et al. "Variational Sequential Monte Carlo" (2018)
  ☆65Updated 6 years ago
• IraKorshunova / bruno
  a deep recurrent model for exchangeable data
  ☆34Updated 4 years ago
• ssydasheng / Neural-Kernel-Network
  Code for "Differentiable Compositional Kernel Learning for Gaussian Processes" https://arxiv.org/abs/1806.04326
  ☆71Updated 6 years ago
• thjashin / solvegp
  Sparse Orthogonal Variational Inference for Gaussian Processes (SOLVE-GP)
  ☆22Updated 3 years ago
• sheqi / GP-RNN_UAI2019
  Implementaion of Gaussian Process Recurrent Neural Networks developed in "Neural Dynamics Discovery via Gaussian Process Recurrent Neura…
  ☆40Updated 2 years ago
• Sohl-Dickstein / Minimum-Probability-Flow-Learning
  Matlab code implementing Minimum Probability Flow Learning.
  ☆68Updated 10 years ago
• mauriziofilippone / deep_gp_random_features
  ☆40Updated 6 years ago
• catniplab / tree_structured_rslds
  Tree-structured recurrent switching linear dynamical systems
  ☆36Updated 4 years ago
• sremes / nssm-gp
  Non-stationary spectral mixture kernels implemented in GPflow
  ☆28Updated 6 years ago
• erichson / ristretto
  Randomized Dimension Reduction Library
  ☆115Updated 4 years ago
• widedeepnetworks / widedeepnetworks
  Code for the paper Gaussian process behaviour in wide deep networks
  ☆46Updated 6 years ago
• wjmaddox / spectralgp
  Code repo for "Function-Space Distributions over Kernels"
  ☆31Updated 4 years ago
• gpapamak / snl
  Sequential Neural Likelihood
  ☆40Updated 5 years ago
• brain-research / l2hmc
  TensorFlow implementation for training MCMC samplers from the paper: Generalizing Hamiltonian Monte Carlo with Neural Network
  ☆182Updated 6 years ago
• dimkal89 / rvae
  ☆38Updated 4 years ago
• cunningham-lab / cb_and_cc
  ☆36Updated 2 years ago
• MFreidank / pysgmcmc
  Bayesian Deep Learning with Stochastic Gradient MCMC Methods
  ☆39Updated 3 years ago
• jayanthkoushik / torch-gel
  Group elastic net implementation in PyTorch.
  ☆45Updated 4 years ago