ermongroup / HyperSPNLinks
PyTorch implementation for "HyperSPNs: Compact and Expressive Probabilistic Circuits", NeurIPS 2021
☆13Updated 3 years ago
Alternatives and similar repositories for HyperSPN
Users that are interested in HyperSPN are comparing it to the libraries listed below
Sorting:
- Scalable training and inference for Probabilistic Circuits☆67Updated last week
- An implementation of EinsumNetworks in PyTorch.☆21Updated last month
- Code for UAI'19: Random Sum-Product Networks: A Simple and Effective Approach to Probabilistic Deep Learning☆37Updated 5 years ago
- ☆52Updated last year
- Supporting code for the paper "Dangers of Bayesian Model Averaging under Covariate Shift"☆33Updated 2 years ago
- A collection of commonly used datasets as benchmarks for density estimation☆24Updated 5 years ago
- Code for "Bayesian Structure Learning with Generative Flow Networks"☆87Updated 3 years ago
- Implicit Deep Adaptive Design (iDAD): Policy-Based Experimental Design without Likelihoods☆19Updated 3 years ago
- Laplace Redux -- Effortless Bayesian Deep Learning☆42Updated 2 weeks ago
- PyTorch linear operators for curvature matrices (Hessian, Fisher/GGN, KFAC, ...)☆40Updated 2 months ago
- An implementation of squared neural families in PyTorch☆14Updated 8 months ago
- ☆15Updated 2 years ago
- Code in support of the paper Continuous Mixtures of Tractable Probabilistic Models☆11Updated 8 months ago
- Code for Knowledge-Adaptation Priors based on the NeurIPS 2021 paper by Khan and Swaroop.☆16Updated 3 years ago
- Code for the paper "Bayesian Neural Network Priors Revisited"☆58Updated 3 years ago
- PyTorch implementation for "Probabilistic Circuits for Variational Inference in Discrete Graphical Models", NeurIPS 2020☆17Updated 3 years ago
- Agustinus' very opiniated publication-ready plotting library☆66Updated last month
- Demos for the paper Generalized Variational Inference (Knoblauch, Jewson & Damoulas, 2019)☆20Updated 6 years ago
- ☆18Updated last month
- a python framework to build, learn and reason about probabilistic circuits and tensor networks☆106Updated last week
- Bayesian active learning with EPIG data acquisition☆32Updated 2 months ago
- Source code for my PhD thesis: Backpropagation Beyond the Gradient☆20Updated 2 years ago
- Mixed Sum-Product Networks: A Deep Architecture for Hybrid Domains☆16Updated 7 years ago
- Posterior Refinement Improves Sample Efficiency in Bayesian Neural Networks☆10Updated 2 years ago
- Differentiable DAG Sampling (ICLR 2022)☆37Updated 2 years ago
- Supporing code for the paper "Bayesian Model Selection, the Marginal Likelihood, and Generalization".☆36Updated 3 years ago
- Official codebase for the paper "Provable concept learning for interpretable predictions using variational inference".☆14Updated 3 years ago
- Bayesian model reduction for probabilistic machine learning☆11Updated 2 months ago
- Repo for our paper "Repulsive deep ensembles are Bayesian"☆19Updated 3 years ago
- This repository contains PyTorch implementations of various random feature maps for dot product kernels.☆21Updated 11 months ago