Alternatives and similar repositories for d3p:

Users that are interested in d3p are comparing it to the libraries listed below

• sarlinpe / Concrete-Dropout
  A clean TensorFlow implementation of Concrete Dropout
  ☆23Updated 7 years ago
• remilepriol / causal-adaptation-speed
  Investigate the speed of adaptation of structural causal models
  ☆16Updated 4 years ago
• aangelopoulos / private_prediction_sets
  Wrap around any model to output differentially private prediction sets with finite sample validity on any dataset.
  ☆17Updated 11 months ago
• ermongroup / SPN_Variational_Inference
  PyTorch implementation for "Probabilistic Circuits for Variational Inference in Discrete Graphical Models", NeurIPS 2020
  ☆16Updated 3 years ago
• csinva / mdl-complexity
  MDL Complexity computations and experiments from the paper "Revisiting complexity and the bias-variance tradeoff".
  ☆18Updated last year
• uber-research / vargp
  Variational Auto-Regressive Gaussian Processes for Continual Learning
  ☆20Updated 3 years ago
• gwgundersen / rflvm
  Random feature latent variable models in Python
  ☆22Updated last year
• aboustati / vargrad
  Code accompanying VarGrad: A Low-Variance Gradient Estimator for Variational Inference
  ☆12Updated 4 years ago
• yannadani / cbed
  Official implementation of the paper "Interventions, Where and How? Experimental Design for Causal Models at Scale", NeurIPS 2022.
  ☆19Updated 2 years ago
• thiery-lab / manifold-mcmc-for-diffusions
  Code accompanying the paper 'Manifold MCMC methods for Bayesian inference in a wide class of diffusion models'
  ☆10Updated last year
• franrruiz / uivi
  Code for Unbiased Implicit Variational Inference (UIVI)
  ☆13Updated 6 years ago
• anirudh9119 / walkback_nips17
  Variational Walkback, NIPS'17
  ☆28Updated 7 years ago
• wooden-spoon / relational-ERM
  Software relating to relational empirical risk minimization
  ☆17Updated 3 years ago
• pierresegonne / VINF
  Repository for DTU Special Course, focusing on Variational Inference using Normalizing Flows (VINF). Supervised by Michael Riis Andersen
  ☆25Updated 4 years ago
• ermongroup / bgm
  Code for "Boosted Generative Models", AAAI 2018.
  ☆20Updated 7 years ago
• anndvision / quince
  Code for Quantifying Ignorance in Individual-Level Causal-Effect Estimates under Hidden Confounding
  ☆21Updated 2 years ago
• realityengines / post_hoc_debiasing
  ☆17Updated 4 years ago
• jmtomczak / git_flow
  General Invertible Transformations for Flow-based Generative Models
  ☆17Updated 4 years ago
• nkeriven / random-graph-gnn
  ☆12Updated 3 years ago
• edwardjhu / improved_wasserstein
  Code for our ICLR Trustworthy ML 2020 workshop paper "Improved Image Wasserstein Attacks and Defenses"
  ☆14Updated 4 years ago
• SebFar / radial_bnn
  Code to accompany the paper Radial Bayesian Neural Networks: Beyond Discrete Support In Large-Scale Bayesian Deep Learning
  ☆33Updated 4 years ago
• HazyResearch / mandoline
  (ICML 2021) Mandoline: Model Evaluation under Distribution Shift
  ☆31Updated 3 years ago
• locuslab / sdp_clustering
  ☆12Updated 4 years ago
• zixu1986 / Doubly_Stochastic_Gradients
  Code for doubly stochastic gradients
  ☆25Updated 10 years ago
• karalets / TyXe
  Library for Bayesian Neural Networks in PyTorch (first version as published in ProbProg2020)
  ☆42Updated 3 years ago
• pyro-ppl / sandbox
  Pyro models and misc examples.
  ☆19Updated 3 years ago
• MatthewWilletts / GM-DGM
  A deep generative model of semi-unsupervised learning
  ☆15Updated 6 years ago
• djsutherland / igms
  Implicit generative models and related stuff based on the MMD, in PyTorch
  ☆16Updated 4 years ago
• ganguli-lab / degrees-of-freedom
  ☆36Updated 3 years ago
• tomlinsonk / choice-set-opt
  Code accompanying our ICML 2020 paper on choice set optimization in group decision-making.
  ☆11Updated 4 years ago