ermongroup / SPN_Variational_InferenceLinks
PyTorch implementation for "Probabilistic Circuits for Variational Inference in Discrete Graphical Models", NeurIPS 2020
☆17Updated 4 years ago
Alternatives and similar repositories for SPN_Variational_Inference
Users that are interested in SPN_Variational_Inference are comparing it to the libraries listed below
Sorting:
- Code in support of the paper Continuous Mixtures of Tractable Probabilistic Models☆11Updated last year
- ☆53Updated 2 years ago
- A minimal implementation of a VAE with BinConcrete (relaxed Bernoulli) latent distribution in TensorFlow.☆22Updated 5 years ago
- This repository provides open-source code for sparse continuous distributions and corresponding Fenchel-Young losses.☆16Updated 2 years ago
- [NeurIPS'19] Deep Equilibrium Models Jax Implementation☆42Updated 5 years ago
- ☆50Updated 5 years ago
- ☆18Updated 3 years ago
- Estimating Gradients for Discrete Random Variables by Sampling without Replacement☆40Updated 5 years ago
- Code to minimize the Variational Contrastive Divergence (VCD)☆29Updated 6 years ago
- Random feature latent variable models in Python☆23Updated 2 years ago
- Bayesian model reduction for probabilistic machine learning☆11Updated 5 months ago
- Pytorch code for Sampling in Combinatorial Spaces with SurVAE Flow Augmented MCMC☆11Updated 4 years ago
- Tensorflow implementation and notebooks for Implicit Maximum Likelihood Estimation☆67Updated 3 years ago
- Monotone operator equilibrium networks☆54Updated 5 years ago
- A public repository for our paper, Rao-Blackwellized Stochastic Gradients for Discrete Distributions☆22Updated 6 years ago
- Implementation of Nonparametric Hamiltonian Monte Carlo☆13Updated 2 years ago
- Recursive Bayesian Networks☆11Updated 6 months ago
- Investigate the speed of adaptation of structural causal models☆15Updated 4 years ago
- Code for UAI'19: Random Sum-Product Networks: A Simple and Effective Approach to Probabilistic Deep Learning☆37Updated 5 years ago
- Code accompanying VarGrad: A Low-Variance Gradient Estimator for Variational Inference☆12Updated 5 years ago
- Implicit Deep Adaptive Design (iDAD): Policy-Based Experimental Design without Likelihoods☆21Updated 3 years ago
- Code for Unbiased Implicit Variational Inference (UIVI)☆15Updated 6 years ago
- ☆54Updated last year
- A Scalable Approximate Method for Probabilistic Neurosymbolic Inference☆16Updated 10 months ago
- ☆15Updated 3 years ago
- Official code for UnICORNN (ICML 2021)☆28Updated 4 years ago
- Computing the eigenvalues of Neural Tangent Kernel and Conjugate Kernel (aka NNGP kernel) over the boolean cube☆47Updated 6 years ago
- [AAAI 2020 Oral] Low-variance Black-box Gradient Estimates for the Plackett-Luce Distribution☆39Updated 4 years ago
- Neural Fixed-Point Acceleration for Convex Optimization☆29Updated 3 years ago
- Implementation of deep implicit attention in PyTorch☆65Updated 4 years ago