Alternatives and similar repositories for keras-lipschitz-networks

Users that are interested in keras-lipschitz-networks are comparing it to the libraries listed below

• siplab-gt / VAELLS
  Code for "Variational Autoencoder with Learned Latent Structure"
  ☆34Updated 4 years ago
• cambridge-mlg / DUN
  Code for "Depth Uncertainty in Neural Networks" (https://arxiv.org/abs/2006.08437)
  ☆78Updated 2 years ago
• cambridge-mlg / cnn-gp
  Pytorch version of "Deep Convolutional Networks as shallow Gaussian Processes" by Adrià Garriga-Alonso, Carl Rasmussen and Laurence Aitch…
  ☆32Updated 5 years ago
• fpcasale / GPPVAE
  Gaussian Process Prior Variational Autoencoder
  ☆86Updated 6 years ago
• cagatayyildiz / ODE2VAE
  ODE2VAE: Deep generative second order ODEs with Bayesian neural networks
  ☆130Updated last year
• bobby-he / bayesian-ntk
  Code to accompany paper 'Bayesian Deep Ensembles via the Neural Tangent Kernel'
  ☆26Updated 4 years ago
• LCAS / RKN
  ☆47Updated 3 years ago
• crisbodnar / ndp
  Official code for the ICLR 2021 paper Neural ODE Processes
  ☆75Updated 3 years ago
• Jiacheng-Zhu-AIML / WGPOT
  The Wasserstein Distance and Optimal Transport Map of Gaussian Processes
  ☆52Updated 5 years ago
• massastrello / awesome-implicit-neural-models
  ☆105Updated 4 years ago
• facebookresearch / rcpm
  Riemannian Convex Potential Maps
  ☆67Updated 2 years ago
• EmilienDupont / neural-processes
  Pytorch implementation of Neural Processes for functions and images
  ☆234Updated 3 years ago
• guxd / deepHMM
  A PyTorch implementation of a Deep Hidden Markov Model [Structured Inference Networks for Nonlinear State Space Models]
  ☆59Updated last year
• TeaPearce / Bayesian_NN_Ensembles
  AISTATS paper 'Uncertainty in Neural Networks: Approximately Bayesian Ensembling'
  ☆90Updated 5 years ago
• hichamjanati / spatio-temporal-alignements
  Spatio-temporal alignements: Optimal transport in space and time
  ☆48Updated 7 months ago
• nikitadurasov / masksembles
  Official repository for the paper "Masksembles for Uncertainty Estimation" (CVPR 2021).
  ☆102Updated 2 weeks ago
• ratschlab / bnn_priors
  Code for the paper "Bayesian Neural Network Priors Revisited"
  ☆58Updated 4 years ago
• microsoft / deterministic-variational-inference
  Sample code for running deterministic variational inference to train Bayesian neural networks
  ☆100Updated 7 years ago
• georgiosarvanitidis / geometric_ml
  This repository contains code for applying Riemannian geometry in machine learning.
  ☆78Updated 4 years ago
• y0ast / deterministic-uncertainty-quantification
  Code for "Uncertainty Estimation Using a Single Deep Deterministic Neural Network"
  ☆273Updated 3 years ago
• skolouri / swgmm
  Sliced Wasserstein Distance for Learning Gaussian Mixture Models
  ☆66Updated 2 years ago
• tiskw / random-fourier-features
  Implementation of random Fourier features for kernel method, like support vector machine and Gaussian process model
  ☆102Updated last year
• CUAI / Neural-Manifold-Ordinary-Differential-Equations
  [NeurIPS 2020] Neural Manifold Ordinary Differential Equations (https://arxiv.org/abs/2006.10254)
  ☆121Updated 2 years ago
• AmirTag / OT-ICNN
  Learning the optimal transport map via input convex neural neworks
  ☆42Updated 5 years ago
• ParthaEth / Regularized_autoencoders-RAE-
  ☆125Updated 2 years ago
• jambo6 / neuralRDEs
  Code for: "Neural Rough Differential Equations for Long Time Series", (ICML 2021)
  ☆120Updated 4 years ago
• yliess86 / BayeFormers
  General API for Deep Bayesian Variational Inference by Backpropagation. The repository has been designed to work with Transformers like a…
  ☆45Updated 5 years ago
• ghliu / snopt
  Second-Order Neural ODE Optimizer, NeurIPS 2021 spotlight
  ☆55Updated 4 years ago
• dimkal89 / rvae
  ☆37Updated 5 years ago
• hughsalimbeni / DGPs_with_IWVI
  Deep Gaussian Processes with Importance-Weighted Variational Inference
  ☆39Updated 6 years ago