dimarkov / bmr4pml
Bayesian model reduction for probabilistic machine learning
☆10Updated this week
Alternatives and similar repositories for bmr4pml:
Users that are interested in bmr4pml are comparing it to the libraries listed below
- Flexible Inference for Predictive Coding Networks in JAX.☆31Updated 2 weeks ago
- PyTorch implementation for "Probabilistic Circuits for Variational Inference in Discrete Graphical Models", NeurIPS 2020☆17Updated 3 years ago
- The implementation of "The Kanerva Machine" with Pytorch and Pyro☆12Updated 6 years ago
- repo for code for paper on general theory associative memory models☆18Updated 2 years ago
- On efficient computation in active inference☆16Updated 9 months ago
- Active inference implementation of dynamic multi-armed bandits☆19Updated last year
- The Energy Transformer block, in JAX☆56Updated last year
- General framework for Bayesian inversion of continuous hierarchical models☆10Updated 3 years ago
- This is a collection of code samples aimed at illustrating temporal parallelization methods for sequential data.☆31Updated last year
- Code for "Bayesian Structure Learning with Generative Flow Networks"☆84Updated 2 years ago
- ☆9Updated last month
- Official repository for the paper "Neural Differential Equations for Learning to Program Neural Nets Through Continuous Learning Rules" (…☆20Updated 2 years ago
- Code in support of the paper Continuous Mixtures of Tractable Probabilistic Models☆12Updated 5 months ago
- [NeurIPS'19] Deep Equilibrium Models Jax Implementation☆39Updated 4 years ago
- ☆12Updated last year
- A Scalable Approximate Method for Probabilistic Neurosymbolic Inference☆14Updated last month
- Variational Reinforcement Learning☆16Updated 7 months ago
- ☆18Updated 3 years ago
- ☆14Updated 3 years ago
- Loopy belief propagation for factor graphs on discrete variables, in JAX!☆65Updated 5 months ago
- Official code for UnICORNN (ICML 2021)☆27Updated 3 years ago
- Tree-structured recurrent switching linear dynamical systems☆36Updated 4 years ago
- Implicit Deep Adaptive Design (iDAD): Policy-Based Experimental Design without Likelihoods☆19Updated 3 years ago
- ☆16Updated 6 months ago
- A PyTorch implementation of a Generative Flow Network (GFlowNet) proposed by Bengio et al. (2021)☆42Updated last year
- Stochastic Gradient Langevin Dynamics for Bayesian learning☆31Updated 3 years ago
- Kernel Identification Through Transformers☆12Updated last year
- Approximate Inference Turns Deep Networks into Gaussian Processes (dnn2gp)☆48Updated 5 years ago
- Variational Auto-Regressive Gaussian Processes for Continual Learning☆21Updated 3 years ago
- ☆13Updated 2 years ago