Collecting research materials on energy/entropy based models
🍓 Simulation-free, GPU-first generative modeling in PyTorch ⚡ Composable primitives for scalable, stable training of modern EBMs, diffusion, flow matching, and Schrödinger bridges.
Restricted Boltzmann Machine for collaborative filtering of movies.
Python implementation of Restricted Boltzmann Machine (RBM). And an example on MNIST dataset.
Official code for paper: Conservative objective models are a special kind of contrastive divergence-based energy model
Tutorial project for learning Convolutional Restricted Boltzmann Machines with Genetic Algorithm, Genetic Programming, PyTorch examples, notebooks, and a PyQt GUI.
Energy-based (Ising/Boltzmann) learning substrate for parity-3 — can a local, physics-native contrastive rule both compute and learn the couplings? Part of the Physical Learning Substrates portfolio.
The functionality of this repository has been integrated into karasier/FastNeurons.
PyTorch implementation of a Masked Gaussian-Bernoulli RBM (GBRBM) for collaborative filtering, featuring masked CD-k training, active-item weight decay, and leakage-free evaluation.
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