pilancilab / scnnLinks
Scalable Convex Neural Networks
☆24Updated 3 months ago
Alternatives and similar repositories for scnn
Users that are interested in scnn are comparing it to the libraries listed below
Sorting:
- The Energy Transformer block, in JAX☆59Updated last year
- Loopy belief propagation for factor graphs on discrete variables in JAX☆154Updated 9 months ago
- Parameter-Free Optimizers for Pytorch☆130Updated last year
- ☆20Updated 10 months ago
- Flexible Inference for Predictive Coding Networks in JAX.☆53Updated last month
- Official repository for the paper "Neural Differential Equations for Learning to Program Neural Nets Through Continuous Learning Rules" (…☆23Updated last month
- ☆192Updated last month
- Unofficial but Efficient Implementation of "Mamba: Linear-Time Sequence Modeling with Selective State Spaces" in JAX☆85Updated last year
- Riemannian Optimization Using JAX☆51Updated last year
- Agustinus' very opiniated publication-ready plotting library☆67Updated 3 months ago
- Repo for the paper "Landscape Surrogate Learning Decision Losses for Mathematical Optimization Under Partial Information"☆36Updated 2 years ago
- Hierarchical Associative Memory User Experience☆102Updated 3 weeks ago
- ☆52Updated last month
- Bayesian model reduction for probabilistic machine learning☆11Updated last month
- Scalable training and inference for Probabilistic Circuits☆70Updated 2 weeks ago
- Stochastic Automatic Differentiation library for PyTorch.☆205Updated 11 months ago
- Bayesian inference with Python and Jax.☆34Updated 2 years ago
- About A collection of AWESOME things about information geometry Topics☆164Updated last year
- ☆15Updated 4 years ago
- Code for "Bayesian Structure Learning with Generative Flow Networks"☆87Updated 3 years ago
- Code for minimum-entropy coupling.☆32Updated last year
- Parallelizing non-linear sequential models over the sequence length☆53Updated last month
- A general-purpose, deep learning-first library for constrained optimization in PyTorch☆135Updated last month
- Recursive Bayesian Estimation (Sequential / Online Inference)☆59Updated last year
- Code for verifying deep neural feature ansatz☆19Updated 2 years ago
- Deep Networks Grok All the Time and Here is Why☆37Updated last year
- A Python package for generating concise, high-quality summaries of a probability distribution☆53Updated 4 months ago
- ☆32Updated 10 months ago
- Brain-Inspired Modular Training (BIMT), a method for making neural networks more modular and interpretable.☆172Updated 2 years ago
- Omnigrok: Grokking Beyond Algorithmic Data☆60Updated 2 years ago