gebob19 / introduction_to_normalizing_flowsLinks
Jupyter Notebook corresponding to 'Going with the Flow: An Introduction to Normalizing Flows'
☆26Updated 4 years ago
Alternatives and similar repositories for introduction_to_normalizing_flows
Users that are interested in introduction_to_normalizing_flows are comparing it to the libraries listed below
Sorting:
- Neural likelihood-free methods in PyTorch.☆39Updated 5 years ago
- PyTorch implementation of Bidirectional Monte Carlo, Annealed Importance Sampling, and Hamiltonian Monte Carlo.☆52Updated 4 years ago
- A minimal implementation of a VAE with BinConcrete (relaxed Bernoulli) latent distribution in TensorFlow.☆22Updated 5 years ago
- PyTorch implementation of Continuously Indexed Flows paper, with many baseline normalising flows☆31Updated 3 years ago
- Repository for DTU Special Course, focusing on Variational Inference using Normalizing Flows (VINF). Supervised by Michael Riis Andersen☆25Updated 4 years ago
- ☆53Updated 10 months ago
- General Invertible Transformations for Flow-based Generative Models☆18Updated 4 years ago
- ☆37Updated 5 years ago
- Riemannian Convex Potential Maps☆67Updated 2 years ago
- ☆29Updated 3 years ago
- Normalizing Flows in Jax☆108Updated 4 years ago
- Code for the Thermodynamic Variational Objective☆26Updated 2 years ago
- code for "Semi-Discrete Normalizing Flows through Differentiable Tessellation"☆26Updated 2 years ago
- We got a stew going!☆27Updated last year
- Official code for UnICORNN (ICML 2021)☆27Updated 3 years ago
- Code for "'Hey, that's not an ODE:' Faster ODE Adjoints via Seminorms" (ICML 2021)☆87Updated 2 years ago
- Code for the paper Semi-Conditional Normalizing Flows for Semi-Supervised Learning☆27Updated 3 years ago
- Stochastic Gradient Langevin Dynamics for Bayesian learning☆31Updated 3 years ago
- Code accompanying VarGrad: A Low-Variance Gradient Estimator for Variational Inference☆12Updated 4 years ago
- repo for paper: Adaptive Checkpoint Adjoint (ACA) method for gradient estimation in neural ODE☆55Updated 4 years ago
- ☆17Updated 4 years ago
- Code for "Accelerating Natural Gradient with Higher-Order Invariance"☆30Updated 5 years ago
- Random feature latent variable models in Python☆22Updated last year
- Euclidean Wasserstein-2 optimal transportation☆47Updated last year
- Composable kernels for scikit-learn implemented in JAX.☆43Updated 4 years ago
- Experiments for Meta-Learning Symmetries by Reparameterization☆56Updated 4 years ago
- Normalizing Flows using JAX☆83Updated last year
- ☆36Updated 2 years ago
- Computing the eigenvalues of Neural Tangent Kernel and Conjugate Kernel (aka NNGP kernel) over the boolean cube☆47Updated 5 years ago
- BIVA: A Very Deep Hierarchy of Latent Variables forGenerative Modeling☆29Updated 5 years ago