gugarosa / learnergy
💡 Learnergy is a Python library for energy-based machine learning models.
☆65Updated 2 weeks ago
Alternatives and similar repositories for learnergy:
Users that are interested in learnergy are comparing it to the libraries listed below
- Library for learning and inference with Sum-product Networks utilizing TensorFlow 2.x and Keras☆48Updated 3 years ago
- Massively Parallel and Asynchronous Architecture for Logic-based AI☆41Updated 2 years ago
- A minimal implementation of a VAE with BinConcrete (relaxed Bernoulli) latent distribution in TensorFlow.☆21Updated 5 years ago
- [NeurIPS 2020] Neural Manifold Ordinary Differential Equations (https://arxiv.org/abs/2006.10254)☆117Updated last year
- TensorLy-Torch: Deep Tensor Learning with TensorLy and PyTorch☆77Updated 9 months ago
- A custom PyTorch layer that is capable of implementing extremely wide and sparse linear layers efficiently☆49Updated last year
- Normalizing Flows using JAX☆83Updated last year
- Source code for ICLR 2020 paper: "Learning to Guide Random Search"☆39Updated 6 months ago
- Code for: "Neural Rough Differential Equations for Long Time Series", (ICML 2021)☆116Updated 3 years ago
- BIVA: A Very Deep Hierarchy of Latent Variables forGenerative Modeling☆29Updated 5 years ago
- Composable kernels for scikit-learn implemented in JAX.☆43Updated 4 years ago
- Documentation:☆119Updated last year
- Tree Approximate Message Passing☆30Updated 10 months ago
- Code Repo for "Subspace Inference for Bayesian Deep Learning"☆83Updated 9 months ago
- Relative gradient optimization of the Jacobian term in unsupervised deep learning, NeurIPS 2020☆21Updated 3 years ago
- Graph Learning with JAX☆14Updated 2 years ago
- CHOP: An optimization library based on PyTorch, with applications to adversarial examples and structured neural network training.☆77Updated last year
- Official repository for the paper "Can You Learn an Algorithm? Generalizing from Easy to Hard Problems with Recurrent Networks"☆60Updated 3 years ago
- Library for Bayesian Neural Networks in PyTorch (first version as published in ProbProg2020)☆42Updated 3 years ago
- ☆68Updated last year
- Padé Activation Units: End-to-end Learning of Activation Functions in Deep Neural Network☆64Updated 4 years ago
- Code for "'Hey, that's not an ODE:' Faster ODE Adjoints via Seminorms" (ICML 2021)☆86Updated 2 years ago
- Bayesian algorithm execution (BAX)☆49Updated 3 years ago
- Codebase for Learning Invariances in Neural Networks☆94Updated 2 years ago
- LaTeX source code for the slides☆23Updated 3 years ago
- ☆36Updated 2 years ago
- Repository for DTU Special Course, focusing on Variational Inference using Normalizing Flows (VINF). Supervised by Michael Riis Andersen☆25Updated 4 years ago
- Updates of Equilibrium Prop Match Gradients of Backprop Through Time in an RNN with Static Input (NeurIPS 2019)☆12Updated last year
- PyHopper is a hyperparameter optimizer, made specifically for high-dimensional problems arising in machine learning research.☆86Updated last year
- Implementation of deep implicit attention in PyTorch☆65Updated 3 years ago