Alternatives and similar repositories for universal-divergence

Users that are interested in universal-divergence are comparing it to the libraries listed below

• mfederici / dsit
  Implementation of the models and datasets used in "An Information-theoretic Approach to Distribution Shifts"
  ☆25Updated 3 years ago
• nhartland / KL-divergence-estimators
  Testing methods for estimating KL-divergence from samples.
  ☆64Updated 3 months ago
• microsoft / conservative-uncertainty-estimation-random-priors
  Source code for paper Conservative Uncertainty Estimation By Fitting Prior Networks (ICLR 2020)
  ☆21Updated 2 years ago
• izmailovpavel / bnn_covariate_shift
  Supporting code for the paper "Dangers of Bayesian Model Averaging under Covariate Shift"
  ☆33Updated 2 years ago
• wgrathwohl / LSD
  Official Release of "Learning the Stein Discrepancy for Training and Evaluating Energy-Based Models without Sampling"
  ☆49Updated 4 years ago
• bobby-he / bayesian-ntk
  Code to accompany paper 'Bayesian Deep Ensembles via the Neural Tangent Kernel'
  ☆26Updated 4 years ago
• team-approx-bayes / fromp
  Contains code for the NeurIPS 2020 paper by Pan et al., "Continual Deep Learning by FunctionalRegularisation of Memorable Past"
  ☆44Updated 4 years ago
• federicobergamin / Variational-Inference-with-Normalizing-Flows
  Personal implementation of "Variational Inference with Normalizing Flows" by [Rezende, et al., 2015] in PyTorch
  ☆22Updated 5 years ago
• wjmaddox / spectralgp
  Code repo for "Function-Space Distributions over Kernels"
  ☆31Updated 4 years ago
• mrojascarulla / causal_transfer_learning
  ☆32Updated 6 years ago
• mingzhang-yin / ARM-gradient
  Low-variance, efficient and unbiased gradient estimation for optimizing models with binary latent variables. (ICLR 2019)
  ☆28Updated 6 years ago
• YingzhenLi / SteinGrad
  Code release for the ICLR paper
  ☆20Updated 7 years ago
• noahgolmant / SGLD
  Stochastic Gradient Langevin Dynamics for Bayesian learning
  ☆32Updated 3 years ago
• ermongroup / f-dre
  Featurized Density Ratio Estimation
  ☆20Updated 3 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
• MichaelArbel / GeneralizedEBM
  ☆54Updated 11 months ago
• StanfordASL / moca
  ☆32Updated 2 years ago
• team-approx-bayes / kpriors
  Code for Knowledge-Adaptation Priors based on the NeurIPS 2021 paper by Khan and Swaroop.
  ☆16Updated 3 years ago
• wjmaddox / drbayes
  Code Repo for "Subspace Inference for Bayesian Deep Learning"
  ☆82Updated last year
• team-approx-bayes / dnn2gp
  Approximate Inference Turns Deep Networks into Gaussian Processes (dnn2gp)
  ☆48Updated 5 years ago
• dilinwang820 / nonlinear_svgd
  Nonlinear SVGD for Learning Diversified Mixture Models
  ☆13Updated 6 years ago
• lxuechen / BDMC
  PyTorch implementation of Bidirectional Monte Carlo, Annealed Importance Sampling, and Hamiltonian Monte Carlo.
  ☆52Updated 4 years ago
• kakaobrain / irm-empirical-study
  An Empirical Study of Invariant Risk Minimization
  ☆27Updated 4 years ago
• franrruiz / vcd_divergence
  Code to minimize the Variational Contrastive Divergence (VCD)
  ☆29Updated 6 years ago
• dtak / ocbnn-public
  General purpose library for BNNs, and implementation of OC-BNNs in our 2020 NeurIPS paper.
  ☆38Updated 3 years ago
• SebFar / radial_bnn
  Code to accompany the paper Radial Bayesian Neural Networks: Beyond Discrete Support In Large-Scale Bayesian Deep Learning
  ☆33Updated 5 years ago
• AMLab-Amsterdam / FNP
  Implementation of the Functional Neural Process models
  ☆43Updated 4 years ago
• ermongroup / f-EBM
  Code for "Training Deep Energy-Based Models with f-Divergence Minimization" ICML 2020
  ☆36Updated 2 years ago
• gd-zhang / noisy-K-FAC
  Natural Gradient, Variational Inference
  ☆29Updated 5 years ago
• jinxu06 / metafun-tensorflow
  Code for "MetaFun: Meta-Learning with Iterative Functional Updates"
  ☆14Updated 4 years ago