Python Conditional-vae Resources

The Official Pytorch and JAX implementation of "Efficient-VDVAE: Less is more" Arxiv preprint Louay Hazami   ·   Rayhane Mama   ·   Ragavan Thurairatn

Autoregressive Image Generation using Residual Quantization (CVPR 2022) The official implementation of "Autoregressive Image Generation using Residual

03_Python_Flow_Control Introduction 👋 The control flow statements are an essential part of the Python programming language. A control flow statement

ChemRxiv | [Paper] XXX DeepStruc Welcome to DeepStruc, a Deep Generative Model (DGM) that learns the relation between PDF and atomic structure and the

cim-misspelling Pytorch implementation of Context-Sensitive Spelling Correction of Clinical Text via Conditional Independence, CHIL 2022. This model (

Conditional Gradients For The Approximately Vanishing Ideal Code for the paper: Wirth, E., and Pokutta, S. (2022). Conditional Gradients for the Appro

Split-VAE Split Variational AutoEncoder Introduction This repository contains and implemementation of a Split Variational AutoEncoder (SVAE). In a SVA

Conditional Motion In-Betweening (CMIB) Official implementation of paper: Conditional Motion In-betweeening. Paper(arXiv) | Project Page | YouTube in-

Regression Transformer Codebase to experiment with a hybrid Transformer that combines conditional sequence generation with regression . Development se

Probabilistic U-Net + **Update** + An improved Model (the Hierarchical Probabilistic U-Net) + LIDC crops is now available. See below. Re-implementatio

Pytorch implementation of the paper "Enhancing Content Preservation in Text Style Transfer Using Reverse Attention and Conditional Layer Normalization"

This repository contains the official code of OSTAR in "Mapping Conditional Distributions for Domain Adaptation Under Generalized Target Shift" (ICLR 2022).

Tutorial Repository with a minimal example for showing how to deploy training across various compute infrastructure.

Implementation for "Conditional entropy minimization principle for learning domain invariant representation features". The code is reproduced from thi

Dynamic VAE frame Automatic feature extraction can be achieved by probability di

Collapse by Conditioning: Training Class-conditional GANs with Limited Data Moha

This is a library for simulate probability theory problems specialy conditional probability. It is also useful to create custom single or joint distribution with specific PMF or PDF to get probability table and genearte data based on probability function.

NCSR: Noise Conditional Flow Model for Learning the Super-Resolution Space Official NCSR training PyTorch Code for the CVPR2021 workshop paper "Noise

This code implements the paper, Kim et al. (2021). Imputing Qualitative Attributes for Trip Chains Extracted from Smart Card Data Using a Conditional Generative Adversarial Network. Transportation Research Part C. Under Review.

Pose with Style: Detail-Preserving Pose-Guided Image Synthesis with Conditional StyleGAN [Paper] [Project Website] [Output resutls] Official Pytorch i

Source codes for Improved Few-Shot Visual Classification (CVPR 2020), Enhancing Few-Shot Image Classification with Unlabelled Examples (WACV 2022) and Beyond Simple Meta-Learning: Multi-Purpose Models for Multi-Domain, Active and Continual Few-Shot Learning (TPAMI 2022 - in submission)

NNR and global probabilities estimation and analysis in peptides or protein fragments This module calculates global and NNR conformation dependent pro

Status: Archive (code is provided as-is, no updates expected) Jukebox Code for "Jukebox: A Generative Model for Music" Paper Blog Explorer Colab Insta

CSDI This is the github repository for the NeurIPS 2021 paper "CSDI: Conditional Score-based Diffusion Models for Probabilistic Time Series Imputation

GAN Compression project | paper | videos | slides [NEW!] GAN Compression is accepted by T-PAMI! We released our T-PAMI version in the arXiv v4! [NEW!]

MatchGAN: A Self-supervised Semi-supervised Conditional Generative Adversarial Network This repository is the official implementation of MatchGAN: A S

Net2Net Code accompanying the NeurIPS 2020 oral paper Network-to-Network Translation with Conditional Invertible Neural Networks Robin Rombach*, Patri

Documentation pythae This library implements some of the most common (Variational) Autoencoder models. In particular it provides the possibility to pe

GANs in Action by Jakub Langr and Vladimir Bok List of available code: Chapter 2: Colab, Notebook Chapter 3: Notebook Chapter 4: Notebook Chapter 6: C

jumpdiff jumpdiff is a python library with non-parametric Nadaraya─Watson estimators to extract the parameters of jump-diffusion processes. With jumpd

vae-textures This is an experiment with using variational autoencoders (VAEs) to perform mesh parameterization. This was also my first project using J

The Neural Process Family This repository contains notebook implementations of the following Neural Process variants: Conditional Neural Processes (CN

DR-GAN: Automatic Radial Distortion Rectification Using Conditional GAN in Real-Time Introduction This is official implementation for DR-GAN (IEEE TCS

CTRL - A Conditional Transformer Language Model for Controllable Generation Authors: Nitish Shirish Keskar, Bryan McCann, Lav Varshney, Caiming Xiong,

A Conditional Point Diffusion-Refinement Paradigm for 3D Point Cloud Completion This repo intends to release code for our work: Zhaoyang Lyu*, Zhifeng

OCT-GAN: Neural ODE-based Conditional Tabular GANs (OCT-GAN) Code for reproducing the experiments in the paper: Jayoung Kim*, Jinsung Jeon*, Jaehoon L

Attend, Infer, Repeat: Fast Scene Understanding with Generative Models This is an unofficial Tensorflow implementation of Attend, Infear, Repeat (AIR)

SLAMP: Stochastic Latent Appearance and Motion Prediction Official implementation of the paper SLAMP: Stochastic Latent Appearance and Motion Predicti

Generative Modeling by Estimating Gradients of the Data Distribution This repo contains the official implementation for the NeurIPS 2019 paper Generat

Optimus: the first pre-trained Big VAE language model This repository contains source code necessary to reproduce the results presented in the EMNLP 2

CDAN Code release for "Conditional Adversarial Domain Adaptation" (NIPS 2018) New version: https://github.com/thuml/Transfer-Learning-Library Dataset

BayesOpt-LV Optimizing Value-at-Risk and Conditional Value-at-Risk of Black Box Functions with Lacing Values (LV) About This repository contains the s

Conditional Generation Using Polynomial Expansions Official implementation of the conditional image generation experiments as described on the NeurIPS

Variational Gibbs inference (VGI) This repository contains the research code for Simkus, V., Rhodes, B., Gutmann, M. U., 2021. Variational Gibbs infer

Learning Conditional Invariance through Cycle Consistency This repository provides a basic TensorFlow 1 implementation of the proposed model in our GC

Energy-based Conditional Generative Adversarial Network (ECGAN) This is the code for the NeurIPS 2021 paper "A Unified View of cGANs with and without

SSC-GAN_repo Pytorch implementation for 'Semi-Supervised Single-Stage Controllable GANs for Conditional Fine-Grained Image Generation'.PDF SSC-GAN:Sem

DivCo: Diverse Conditional Image Synthesis via Contrastive Generative Adversarial Network Pytorch implementation for our DivCo. We propose a simple ye

DivNoising: Diversity Denoising with Fully Convolutional Variational Autoencoders Mangal Prakash1, Alexander Krull1,2, Florian Jug2 1Authors contribut

Sylvester normalizing flows for variational inference Pytorch implementation of Sylvester normalizing flows, based on our paper: Sylvester normalizing

CTRL - A Conditional Transformer Language Model for Controllable Generation Authors: Nitish Shirish Keskar, Bryan McCann, Lav Varshney, Caiming Xiong,

corn-ordinal-neuralnet This repository contains the orginal model code and experiment logs for the paper "Deep Neural Networks for Rank Consistent Ord

cppn-gan-vae tensorflow Train Compositional Pattern Producing Network as a Generative Model, using Generative Adversarial Networks and Variational Aut

pix2pix Project | Arxiv | PyTorch Torch implementation for learning a mapping from input images to output images, for example: Image-to-Image Translat

Age Progression/Regression by Conditional Adversarial Autoencoder (CAAE) TensorFlow implementation of the algorithm in the paper Age Progression/Regre

Image De-raining Using a Conditional Generative Adversarial Network [Paper Link] [Project Page] He Zhang, Vishwanath Sindagi, Vishal M. Patel In this

Invertible Conditional GANs This is the implementation of the IcGAN model proposed in our paper: Invertible Conditional GANs for image editing. Novemb

zi2zi: Master Chinese Calligraphy with Conditional Adversarial Networks Introduction Learning eastern asian language typefaces with GAN. zi2zi(字到字, me

Ladder Variational Autoencoders (LVAE) PyTorch implementation of Ladder Variational Autoencoders (LVAE) [1]: where the variational distributions q at

tensorflow-generative-model-collections Tensorflow implementation of various GANs and VAEs. Related Repositories Pytorch version Pytorch version of th

Recurrent Conditional Query Learning (RCQL) This repository contains the Pytorch implementation of One Model Packs Thousands of Items with Recurrent C

Instance-conditional Knowledge Distillation for Object Detection This is a MegEngine implementation of the paper "Instance-conditional Knowledge Disti

Conditional Variational Capsule Network for Open Set Recognition This repository hosts the official code related to "Conditional Variational Capsule N

Energy-based Conditional Generative Adversarial Network (ECGAN) This is the code for the NeurIPS 2021 paper "A Unified View of cGANs with and without

Git repositoty of the manuscript entitled Statistical quantification of confounding bias in predictive modelling by Tamas Spisak The manuscript descri

CKDN The official implementation of the ICCV2021 paper "Learning Conditional Knowledge Distillation for Degraded-Reference Image Quality Assessment" O

Finding Regions of Heterogeneity in Decision-Making via Expected Conditional Covariance Justin Lim, Christina X Ji, Michael Oberst, Saul Blecker, Leor

Introduction This repository is about paper SpeakerGAN , and is unofficially implemented by Mingming Huang ([email protected]), Tiezheng Wang (wtz920729

PyTorch Autoencoders Implementing a Variational Autoencoder (VAE) Series in Pytorch. Inspired by this repository Model List check model paper conferen

DU-VAE This is the pytorch implementation of the paper "Regularizing Variational Autoencoder with Diversity and Uncertainty Awareness" Acknowledgement

Cross-Speaker-Emotion-Transfer - PyTorch Implementation PyTorch Implementation of ByteDance's Cross-speaker Emotion Transfer Based on Speaker Conditio

This is the official code for Multi-attribute Pizza Generator (MPG2): Cross-domain Attribute Control with Conditional StyleGAN. Paper Demo Setup Envir

CondGauss This repository contains PyTorch code for the paper Stochastic Gaussian PAC-Bayes. A novel PAC-Bayesian training method is implemented. Ther

Sparse VAE This repository contains the code for the paper ``Identifiable VAEs via Sparse Decoding''. Data Sources The datasets used in this paper wer

ACTOR Official Pytorch implementation of the paper "Action-Conditioned 3D Human Motion Synthesis with Transformer VAE", ICCV 2021. Please visit our we

Chunked Autoregressive GAN (CARGAN) Official implementation of the paper Chunked Autoregressive GAN for Conditional Waveform Synthesis [paper] [compan

D2C: Diffuison-Decoding Models for Few-shot Conditional Generation Project | Paper PyTorch implementation of D2C: Diffuison-Decoding Models for Few-sh

ST-VAE Multiple style transfer via variational autoencoder By Zhi-Song Liu, Vicky Kalogeiton and Marie-Paule Cani This repo only provides simple testi

ConditionalQA Datasets accompanying the paper ConditionalQA: A Complex Reading Comprehension Dataset with Conditional Answers. Disclaimer This dataset

LSTM-VAE Implementation and Relevant Evaluations Before using any file in this repository, please create two directories under the root directory name

CRFConv This repository is the implementation of "Continuous Conditional Random Field Convolution for Point Cloud Segmentation" 1. Setup 1) Building c

This is the official implementation of our neural-network-based fast diffuse room impulse response generator (FAST-RIR) for generating room impulse responses (RIRs) for a given acoustic environment.

[ICCV'2021] Image Inpainting via Conditional Texture and Structure Dual Generation

PortaSpeech - PyTorch Implementation PyTorch Implementation of PortaSpeech: Portable and High-Quality Generative Text-to-Speech. Model Size Module Nor

PortaSpeech - PyTorch Implementation PyTorch Implementation of PortaSpeech: Portable and High-Quality Generative Text-to-Speech. Model Size Module Nor

Deep-Unsupervised-Domain-Adaptation Pytorch implementation of four neural network based domain adaptation techniques: DeepCORAL, DDC, CDAN and CDAN+E.

CondNet: Conditional Classifier for Scene Segmentation Introduction The fully convolutional network (FCN) has achieved tremendous success in dense vis

Conditional probing: measuring usable information beyond a baseline

pix2pix-pytorch PyTorch implementation of Image-to-Image Translation Using Conditional Adversarial Networks. Based on pix2pix by Phillip Isola et al.

Pytorch Recurrent Variational Autoencoder Model: This is the implementation of Samuel Bowman's Generating Sentences from a Continuous Space with Kim's

DALL-E-Tokenizer Huggingface package for the discrete VAE used for DALL-E.

Hierarchical Conditional Flow: A Unified Framework for Image Super-Resolution and Image Rescaling (HCFlow, ICCV2021) This repository is the official P

Hierarchical Conditional Flow: A Unified Framework for Image Super-Resolution and Image Rescaling (HCFlow, ICCV2021) This repository is the official P

pytorch-generative-model-collections Original : [Tensorflow version] Pytorch implementation of various GANs. This repository was re-implemented with r

CFLOW-AD: Real-Time Unsupervised Anomaly Detection with Localization via Conditional Normalizing Flows WACV 2022 preprint:https://arxiv.org/abs/2107.1

The DETR approach applies the transformer encoder and decoder architecture to object detection and achieves promising performance. In this paper, we handle the critical issue, slow training convergence, and present a conditional cross-attention mechanism for fast DETR training. Our approach is motivated by that the cross-attention in DETR relies highly on the content embeddings and that the spatial embeddings make minor contributions, increasing the need for high-quality content embeddings and thus increasing the training difficulty.

transformers-into-vaes Code for Finetuning Pretrained Transformers into Variational Autoencoders (our submission to NLP Insights Workshop 2021). Gathe

pix2pixHD Project | Youtube | Paper Pytorch implementation of our method for high-resolution (e.g. 2048x1024) photorealistic image-to-image translatio

VAENAR-TTS - PyTorch Implementation PyTorch Implementation of VAENAR-TTS: Variational Auto-Encoder based Non-AutoRegressive Text-to-Speech Synthesis.

Advanced Deep Learning with TensorFlow 2 and Keras (Updated for 2nd Edition)