nhartland / KL-divergence-estimatorsLinks
Testing methods for estimating KL-divergence from samples.
☆69Updated 2 weeks ago
Alternatives and similar repositories for KL-divergence-estimators
Users that are interested in KL-divergence-estimators are comparing it to the libraries listed below
Sorting:
- PyTorch implementation for the ICLR 2020 paper "Understanding the Limitations of Variational Mutual Information Estimators"☆77Updated 5 years ago
- A pytorch implementation of MINE(Mutual Information Neural Estimation)☆350Updated 6 years ago
- Official pytorch implementation of the paper "Bayesian Meta-Learning for the Few-Shot Setting via Deep Kernels" (NeurIPS 2020)☆205Updated 3 years ago
- demonstration of the information bottleneck theory for deep learning☆67Updated 8 years ago
- Classifier based mutual information, conditional mutual information estimation; conditional independence testing☆35Updated 6 years ago
- PyTorch implementation of "Weight Uncertainty in Neural Networks"☆176Updated 3 years ago
- The collection of recent papers about variational inference☆84Updated 6 years ago
- Pytorch implementation of Neural Processes for functions and images☆234Updated 3 years ago
- Reimplementation of Variational Inference with Normalizing Flows (https://arxiv.org/abs/1505.05770)☆239Updated 7 years ago
- This is the source code for Learning Deep Kernels for Non-Parametric Two-Sample Tests (ICML2020).☆51Updated 4 years ago
- Papers for Bayesian-NN☆325Updated 6 years ago
- Code for the paper "Bayesian Neural Network Priors Revisited"☆58Updated 4 years ago
- ☆155Updated 5 years ago
- {KFAC,EKFAC,Diagonal,Implicit} Fisher Matrices and finite width NTKs in PyTorch☆216Updated last week
- Mutual Information Neural Estimation in Pytorch☆345Updated last year
- Code for ICE-BeeM paper - NeurIPS 2020☆87Updated 4 years ago
- Code for the Neural Processes website and replication of 4 papers on NPs. Pytorch implementation.☆227Updated last year
- Deep neural network kernel for Gaussian process☆212Updated 5 years ago
- AISTATS paper 'Uncertainty in Neural Networks: Approximately Bayesian Ensembling'☆90Updated 5 years ago
- Code for paper: SDE-Net: Equipping Deep Neural network with Uncertainty Estimates☆116Updated 5 years ago
- ☆24Updated 4 years ago
- Code for the paper "Disentanglement by Nonlinear ICA with General Incompressible-flow Networks (GIN)" (2020)☆33Updated 4 years ago
- A Python module for estimating divergence between two sets of samples.☆18Updated 2 years ago
- A PyTorch library for two-sample tests☆242Updated last month
- ☆150Updated 3 years ago
- PyTorch implementation of FIM and empirical FIM☆60Updated 7 years ago
- Masked Autoregressive Flow☆218Updated last year
- The codebase for the paper "A Tail-Index Analysis of Stochastic Gradient Noise in Deep Neural Networks"☆25Updated 6 years ago
- code for the paper "Stein Variational Gradient Descent (SVGD): A General Purpose Bayesian Inference Algorithm"☆100Updated 6 years ago
- Random Fourier Features☆50Updated 8 years ago