• Github Code
• Github Code
• Github Code
• Github Code
• Github Code
• here
• Improving Variational Inference with Inverse Autoregressive Flow
• Deep Density Destructors
• Generalized Energy Based Models
• No MCMC for me: Amortized sampling for fast and stable training of energy-based models
• Implicit Generation and Modeling with Energy-Based Models
• Non-linear Independent Components Estimation
• Invertible Generative Modeling using Linear Rational Splines
• Gaussianization Flows
• Flows for simultaneous manifold learning and density estimation
• Your Classifier is Secretly an Energy Based Model and You Should Treat it Like One
• Learning the Stein Discrepancy for Training and Evaluating Energy-Based Models without Sampling
• Flow Contrastive Estimation of Energy-Based Models
• Learning Energy-Based Models by Diffusion Recovery Likelihood
• How to Train Your Energy-Based Models
• Masked Autoencoder for Distribution Estimation
• Variational Inference with Normalizing Flows
• Density estimation using Real NVP - Dickstein, Samy Bengio.
• Multiplicative Normalizing Flows for Variational Bayesian Neural Networks
• Masked Autoregressive Flow for Density Estimation
• Sylvester Normalizing Flow for Variational Inference
• Glow: Generative Flow with Invertible 1x1 Convolutions
• FFJORD: Free-form Continuous Dynamics for Scalable Reversible Generative Models
• Block Neural Autoregressive Flow - De Cao et. al.
• Graph Normalizing Flows
• Normalizing Flows: An Introduction and Review of Current Methods
• Neural Spline Flows
• Normalizing Flows for Probabilistic Modeling and Inference
• VAEBM: A Symbiosis between Variational Autoencoders and Energy-based Models

🛠️ Applications

• Analyzing Inverse Problems with Invertible Neural Networks
• Faster Uncertainty Quantification for Inverse Problems with Conditional Normalizing Flows
• NeuTra-lizing Bad Geometry in Hamiltonian Monte Carlo Using Neural Transport
• SRFlow: Learning the Super-Resolution Space with Normalizing Flow

<img src="assets/pytorch.svg" alt="PyTorch" height="20px"> &nbsp;PyTorch Repos

• `pytorch-flows`
• `normalizing_flows`
• `pytorch_flows` - ircam](https://github.com/acids-ircam)
• `pytorch-normalizing-flows`
• Jul 3, 2020 - [Density Estimation with Neural ODEs](https://torchdyn.readthedocs.io/en/latest/tutorials/07a_continuous_normalizing_flows.html) and [Density Estimation with FFJORDs](https://torchdyn.readthedocs.io/en/latest/tutorials/07b_ffjord.html) by [`torchdyn`](https://torchdyn.readthedocs.io)
• `Normalizing Flows - Introduction (Part 1)`
• Parts 2 and 3 coming later

Others

• `destructive-deep-learning`
• `normalizing_flows_overview.ipynb`

<img src="assets/jax.png" alt="JAX" height="15px"> &nbsp;JAX Repos

• Jul 19, 2019 - [`Neural Transport`](https://pyro.ai/numpyro/examples/neutra) by [numpyro](http://num.pyro.ai/en/stable)

Others

• PRs welcome! - ->

🛠️ Applications

• Sylvester Normalizing Flow for Variational Inference
• Graph Normalizing Flows
• A primer on normalizing flows - dinh.github.io) (Google Brain).
• What are normalizing flows?
• Flow Models - 158-SP20 Deep, Unsupervised Spring Learning,, 2020](https://sites.google.com/view/berkeley-cs294-158-sp20/home) (Berkeley)

🛠️ Applications

• Normalizing Flows
• Flow-based Deep Generative Models
• Part 1

<img src="assets/tensorflow.svg" alt="TensorFlow" height="20px"> &nbsp;TensorFlow Packages

• Jun 22, 2018 - [TensorFlow Probability](https://tensorflow.org/probability)

<img src="assets/jax.png" alt="JAX" height="15px"> &nbsp;JAX Packages

• Mar 9, 2020 - [`NuX`](https://github.com/Information-Fusion-Lab-Umass/NuX) by Information Fusion Labs (UMass)
• Mar 23, 2020 - [`jax-flows`](https://github.com/ChrisWaites/jax-flows) by [Chris Waites](https://chriswaites.com/#)

<img src="assets/pytorch.svg" alt="PyTorch" height="20px"> &nbsp;PyTorch Packages

• `nflows`