braun-steven / simple-einetLinks
An implementation of EinsumNetworks in PyTorch.
☆21Updated 2 weeks ago
Alternatives and similar repositories for simple-einet
Users that are interested in simple-einet are comparing it to the libraries listed below
Sorting:
- ☆52Updated last year
- PyTorch implementation for "HyperSPNs: Compact and Expressive Probabilistic Circuits", NeurIPS 2021☆13Updated 3 years ago
- Scalable training and inference for Probabilistic Circuits☆65Updated 2 weeks ago
- Code for UAI'19: Random Sum-Product Networks: A Simple and Effective Approach to Probabilistic Deep Learning☆37Updated 4 years ago
- Squared Non-monotonic Probabilistic Circuits☆22Updated 4 months ago
- A Python Library for Deep Probabilistic Modeling☆61Updated 7 months ago
- CausalFlows: A library for Causal Normalizing Flows in Pytorch☆21Updated last month
- Code in support of the paper Continuous Mixtures of Tractable Probabilistic Models☆11Updated 7 months ago
- A collection of commonly used datasets as benchmarks for density estimation☆24Updated 5 years ago
- a python framework to build, learn and reason about probabilistic circuits and tensor networks☆101Updated last month
- This repository holds the code for the NeurIPS 2022 paper, Semantic Probabilistic Layers☆27Updated last year
- PAC-Bayes with Backprop - Tighter risk certificates for neural networks☆24Updated 3 years ago
- Bayesian active learning with EPIG data acquisition☆32Updated last month
- Approximate Inference Turns Deep Networks into Gaussian Processes (dnn2gp)☆48Updated 5 years ago
- Codebase for the paper: Not All Neuro-Symbolic Concepts Are Created Equal: Analysis and Mitigation of Reasoning Shortcuts☆19Updated last year
- Bayesian model reduction for probabilistic machine learning☆11Updated last month
- A collection of commonly used datasets as benchmarks for density estimation in MaLe☆19Updated 5 years ago
- PyTorch linear operators for curvature matrices (Hessian, Fisher/GGN, KFAC, ...)☆38Updated last month
- This repository contains code for applying Riemannian geometry in machine learning.☆77Updated 3 years ago
- Code for Knowledge-Adaptation Priors based on the NeurIPS 2021 paper by Khan and Swaroop.☆16Updated 3 years ago
- Code for "Bayesian Structure Learning with Generative Flow Networks"☆87Updated 3 years ago
- ☆11Updated 3 years ago
- Demos for the paper Generalized Variational Inference (Knoblauch, Jewson & Damoulas, 2019)☆20Updated 6 years ago
- Code for the paper: "Independent mechanism analysis, a new concept?"☆24Updated last year
- A curated collection of papers on probabilistic circuits, computational graphs encoding tractable probability distributions.☆50Updated last year
- Mixed Sum-Product Networks: A Deep Architecture for Hybrid Domains☆16Updated 7 years ago
- ☆36Updated 3 years ago
- Supporting code for the paper "Dangers of Bayesian Model Averaging under Covariate Shift"☆33Updated 2 years ago
- PyTorch implementation for "Probabilistic Circuits for Variational Inference in Discrete Graphical Models", NeurIPS 2020☆17Updated 3 years ago
- Repo for our paper "Repulsive deep ensembles are Bayesian"☆19Updated 3 years ago