rgklab / StructuredNNsLinks
Structured Neural Networks
☆15Updated last year
Alternatives and similar repositories for StructuredNNs
Users that are interested in StructuredNNs are comparing it to the libraries listed below
Sorting:
- Materials of the Nordic Probabilistic AI School 2023.☆91Updated 2 years ago
- ☆155Updated 3 years ago
- Official Implementation of "Transformers Can Do Bayesian Inference", the PFN paper☆240Updated last year
- Amortized Inference for Causal Structure Learning, NeurIPS 2022☆69Updated 10 months ago
- CSuite: A Suite of Benchmark Datasets for Causality☆80Updated 2 years ago
- CausalPFN: Amortized Causal Effect Estimation via In-Context Learning☆80Updated last week
- DiBS: Differentiable Bayesian Structure Learning, NeurIPS 2021☆51Updated last year
- Code for "Bayesian Structure Learning with Generative Flow Networks"☆94Updated 3 years ago
- Repo for the Tutorials of Day1-Day2 of the Nordic Probabilistic AI School 2023☆17Updated 2 years ago
- Public dataset repository for the Causal Chamber Project☆53Updated last month
- ☆52Updated last year
- Official repository of the paper "Efficient Neural Causal Discovery without Acyclicity Constraints"☆88Updated last year
- Materials of the Nordic Probabilistic AI School 2022.☆181Updated 3 years ago
- PyTorch-based library for Riemannian Manifold Hamiltonian Monte Carlo (RMHMC) and inference in Bayesian neural networks☆462Updated last year
- Our maintained PFN repository. Come here to train SOTA PFNs.☆122Updated 2 months ago
- Realistic benchmark for different causal inference methods. The realism comes from fitting generative models to data with an assumed caus…☆84Updated 4 years ago
- A Python 3 package for learning Bayesian Networks (DAGs) from data. Official implementation of the paper "DAGMA: Learning DAGs via M-matr…☆137Updated last year
- ☆33Updated 2 years ago
- An experimental language for causal reasoning☆243Updated last week
- A general-purpose, deep learning-first library for constrained optimization in PyTorch☆147Updated last month
- Generating and Imputing Tabular Data via Diffusion and Flow XGBoost Models☆173Updated last year
- Public repo for course material on Bayesian machine learning at ENS Paris-Saclay and Univ Lille☆92Updated 9 months ago
- Light-weighted code for Orthogonal Additive Gaussian Processes☆43Updated last year
- Code for Hidden Markov Nonlinear ICA☆24Updated 4 years ago
- [Experimental] Global causal discovery algorithms☆110Updated last week
- Code for ICE-BeeM paper - NeurIPS 2020☆87Updated 4 years ago
- Code for the paper: Amortized Causal Discovery: Learning to Infer Causal Graphs from Time-Series Data☆220Updated 3 years ago
- Code for the Neural Processes website and replication of 4 papers on NPs. Pytorch implementation.☆227Updated last year
- Code for "Causal autoregressive flows" - AISTATS, 2021☆45Updated 4 years ago
- This library would form a permanent home for reusable components for deep probabilistic programming. The library would form and harness a…☆311Updated 5 months ago