wannesm / PySDD
Python package for Sentential Decision Diagrams (SDD)
☆53Updated 2 months ago
Related projects: ⓘ
- Codebase for VAEL: Bridging Variational Autoencoders and Probabilistic Logic Programming☆19Updated last year
- A curated collection of papers on probabilistic circuits, computational graphs encoding tractable probability distributions.☆47Updated 7 months ago
- The Python PSDD Package☆15Updated last week
- ☆50Updated last year
- This repository holds the code for the NeurIPS 2022 paper, Semantic Probabilistic Layers☆24Updated 9 months ago
- Manipulate NNF (Negation Normal Form) logical sentences☆17Updated last year
- ☆25Updated 7 months ago
- ☆15Updated 5 years ago
- First-order knowledge compilation for lifted probabilistic inference☆11Updated 7 years ago
- A collection of commonly used datasets as benchmarks for density estimation☆24Updated 4 years ago
- Codebase for the paper: Not All Neuro-Symbolic Concepts Are Created Equal: Analysis and Mitigation of Reasoning Shortcuts☆16Updated 6 months ago
- Scalable training and inference for Probabilistic Circuits☆45Updated last week
- ☆16Updated last year
- ☆32Updated 6 months ago
- Experimentation framework for Popper☆18Updated 4 months ago
- Scalable Neural-Probabilistic Answer Set Programming☆17Updated 3 months ago
- ☆19Updated last year
- ☆35Updated last year
- ☆16Updated 2 years ago
- ☆23Updated 3 years ago
- Lernd is ∂ILP (dILP) framework implementation based on Deepmind's paper Learning Explanatory Rules from Noisy Data.☆24Updated last year
- ☆41Updated last year
- Code for "Learning Compositional Rules via Neural Program Synthesis"☆58Updated 3 years ago
- ☆39Updated 10 months ago
- The Neuro-Symbolic Forward Reasoner☆22Updated last year
- Differentiable probabilistic answer set programming☆17Updated 3 weeks ago
- PyPSDD porting to Python 3 + PyTorch equivalent tree construction.☆14Updated last year
- A Scalable Approximate Method for Probabilistic Neurosymbolic Inference☆14Updated last year
- ☆15Updated this week
- Symbolic Reinforcement Learning using Inductive Logic Programming☆61Updated last year