vinsis / understanding-neuralnetworks-pytorch
Understanding nuts and bolts of neural networks with PyTorch
☆32Updated 4 years ago
Alternatives and similar repositories for understanding-neuralnetworks-pytorch:
Users that are interested in understanding-neuralnetworks-pytorch are comparing it to the libraries listed below
- Material for my course: Optimization in Machine Learning☆31Updated 3 years ago
- Some small scale experiments for my blog posts 📝☆79Updated 2 years ago
- Material for my Caltech tutorial on deep learning and tensor methods☆70Updated 6 years ago
- Discontinuous Hamiltonian Monte Carlo in JAX☆41Updated 5 years ago
- PyTorch implementation of Bidirectional Monte Carlo, Annealed Importance Sampling, and Hamiltonian Monte Carlo.☆52Updated 3 years ago
- ☆85Updated 4 years ago
- Repo for the Tutorials of Day1-Day3 of the Nordic Probabilistic AI School 2019 (https://2019.probabilistic.ai/)☆20Updated 5 years ago
- JAX implementation of Learning to learn by gradient descent by gradient descent☆27Updated 4 months ago
- Ἀνατομή is a PyTorch library to analyze representation of neural networks☆62Updated last year
- Pytorch implementation of Variational Dropout Sparsifies Deep Neural Networks☆83Updated 3 years ago
- Materials for class on topics in deep learning (STAT 991, UPenn/Wharton)☆95Updated 2 years ago
- BIVA: A Very Deep Hierarchy of Latent Variables forGenerative Modeling☆29Updated 5 years ago
- Normalizing Flows in Jax☆107Updated 4 years ago
- Learning some numerical linear algebra.☆71Updated 4 years ago
- A tutorial on JAX (https://github.com/google/jax/)☆46Updated 6 years ago
- Jupyter Notebook corresponding to 'Going with the Flow: An Introduction to Normalizing Flows'☆25Updated 3 years ago
- Deep Probabilistic Programming Course @ DIKU☆57Updated 4 years ago
- Toy implementations of some popular ML optimizers using Python/JAX☆44Updated 3 years ago
- A selection of neural network models ported from torchvision for JAX & Flax.☆44Updated 4 years ago
- ☆30Updated 2 years ago
- Code Repo for "Subspace Inference for Bayesian Deep Learning"☆82Updated 8 months ago
- Bayesianize: A Bayesian neural network wrapper in pytorch☆88Updated 9 months ago
- Repository for DTU Special Course, focusing on Variational Inference using Normalizing Flows (VINF). Supervised by Michael Riis Andersen☆25Updated 4 years ago
- Materials of the Nordic Probabilistic AI School 2019.☆129Updated 4 years ago
- ☆35Updated 4 years ago
- Materials for ORIE 7191: Topics in Optimization for Machine Learning☆43Updated 5 years ago
- ☆164Updated 7 months ago
- Stochastic Gradient Langevin Dynamics for Bayesian learning☆30Updated 3 years ago
- ☆28Updated 5 years ago
- Lectures for INFO8004 Advanced Machine Learning, ULiège☆108Updated 2 weeks ago