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10 search results found

Normalizing flows in PyTorch

Deep Generative Models For Natural Language Processing ⭐ 330

DGMs for NLP. A roadmap.

Normalizing Flows ⭐ 255

Neural Spline Flow, RealNVP, Autoregressive Flow, 1x1Conv in PyTorch.

Normalizing flows in PyTorch

Portaspeech ⭐ 211

PyTorch Implementation of PortaSpeech: Portable and High-Quality Generative Text-to-Speech

Code for reproducing Flow ++ experiments

Normalizing Flows ⭐ 135

Implementation of normalizing flows in TensorFlow 2 including a small tutorial.

Net2net ⭐ 128

Network-to-Network Translation with Conditional Invertible Neural Networks

This is project page for the paper "RG-Flow: a hierarchical and explainable flow model based on renormalization group and sparse prior". Paper link: https://arxiv.org/abs/2010.00029

Nanoflow ⭐ 53

PyTorch implementation of the paper "NanoFlow: Scalable Normalizing Flows with Sublinear Parameter Complexity."

Vae_householder_flow ⭐ 53

Code for the paper "Improving Variational Auto-Encoders using Householder Flow" (https://arxiv.org/abs/1611.09630)

Reinforcement learning algorithms in RLlib

Neuralrg ⭐ 51

Pytorch source code for arXiv paper Neural Network Renormalization Group, a generative model using variational renormalization group and normalizing flow.

Biology-driven deep generative model for cell-type annotation in cytometry. Scyan is an interpretable model that also corrects batch-effect and can be used for debarcoding or population discovery.

Minified Generative Models ⭐ 24

Bare-bones implementations of some generative models in Jax: diffusion, normalizing flows, consistency models, flow matching, (beta)-VAEs.

Continuous Time Flow Process ⭐ 21

PyTorch code of "Modeling Continuous Stochastic Processes with Dynamic Normalizing Flows" (NeurIPS 2020)

Tf Invertible Resnet ⭐ 19

A TensorFlow implementation of Invertible Residual Networks

Probaforms ⭐ 16

Conditional normalizing flows (NFs), conditional GANs, and conditional variational autoencoders (CVAEs) with sklearn-like interface

Pde Surrogate ⭐ 15

Physics-constrained deep learning for high-dimensional surrogate modeling and uncertainty quantification without labeled data

Pytorch Nice ⭐ 12

Implementation of non-linear independent components estimation (NICE) in pytorch

Dpf Nets ⭐ 11

Flow-based generative model for 3D point clouds.

Ffjord Rnode ⭐ 8

Regularized Neural ODEs (RNODE)

Normalizing Flows ⭐ 5

Modern normalizing flows in Python. Simple to use and easily extensible.

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