april-tools / gekcsLinks
How to Turn Your Knowledge Graph Embeddings into Generative Models
☆53Updated last year
Alternatives and similar repositories for gekcs
Users that are interested in gekcs are comparing it to the libraries listed below
Sorting:
- ☆34Updated 11 months ago
- PyTorch Explain: Interpretable Deep Learning in Python.☆163Updated last year
- Official implementation of Inductive Logical Query Answering in Knowledge Graphs (NeurIPS 2022)☆46Updated 3 years ago
- Code for "Bayesian Structure Learning with Generative Flow Networks"☆92Updated 3 years ago
- ☆80Updated 2 years ago
- Codebase for VAEL: Bridging Variational Autoencoders and Probabilistic Logic Programming☆22Updated 2 years ago
- PyG re-implementation of Neural Bellman-Ford Networks (NeurIPS 2021)☆76Updated 3 years ago
- Code for paper Fully Hyperbolic Neural Networks☆84Updated 2 years ago
- Official PyTorch implementation of Hyperbolic Neural Networks++☆78Updated 4 years ago
- Simplicial neural networks (SNNs), a generalization of graph neural networks to data that live on a class of topological spaces called si…☆81Updated 4 years ago
- A Scalable Approximate Method for Probabilistic Neurosymbolic Inference☆16Updated 9 months ago
- Implementation of "SALSA-CLRS: A Sparse and Scalable Benchmark for Algorithmic Reasoning". SALSA-CLRS is an extension to the original clr…☆20Updated last year
- The Energy Transformer block, in JAX☆61Updated last year
- Official source code for "Graph Neural Networks for Learning Equivariant Representations of Neural Networks". In ICLR 2024 (oral).☆83Updated last year
- a python framework to build, learn and reason about probabilistic circuits and tensor networks☆122Updated last week
- ☆121Updated 2 years ago
- A Python Library for Deep Probabilistic Modeling☆62Updated last year
- PyTorch implementation of Logic Tensor Networks, a Neural-Symbolic framework.☆29Updated last year
- Logic Explained Networks is a python repository implementing explainable-by-design deep learning models.☆51Updated 2 years ago
- ☆13Updated 5 months ago
- Updated code base for GlanceNets: Interpretable, Leak-proof Concept-based models☆25Updated 2 years ago
- We integrate discrete diffusion models with neurosymbolic predictors for scalable and calibrated learning and reasoning☆51Updated this week
- Library that contains implementations of machine learning components in the hyperbolic space☆142Updated last year
- ☆11Updated 2 years ago
- ZeroC is a neuro-symbolic method that trained with elementary visual concepts and relations, can zero-shot recognize and acquire more com…☆32Updated 2 years ago
- Official implementation of A* Networks☆149Updated 2 years ago
- ☆66Updated 7 months ago
- ☆39Updated 2 years ago
- Scalable training and inference for Probabilistic Circuits☆86Updated last week
- We develop benchmarks and analysis tools to evaluate the causal reasoning abilities of LLMs.☆132Updated last year