A VAEGAN based generative model for multiclass imbalanced learning

Tensorflow implementation of the paper 'Deblurring Variational Autoencoders with Short-Time Fourier Transform'

The official Pytorch implementation of the paper "Fourier Transformer: Fast Long Range Modeling by Removing Sequence Redundancy with FFT Operator" (ACL 2023 Findings)

CAE-GAN: Core Attributes Enhanced Generative Adversarial Network for Robust Image Enhancement

try out bearing fault diagnosis with semi-supervised vae

Implement GANs to generate time-series signals for imbalanced learning problem. The experiments are conducted using CWRU bearing data.

TFGAN: Time and Frequency Domain Based Generative Adversarial Network for High-fidelity Speech Synthesis

Pytorch implementation of the Variational Recurrent Neural Network (VRNN).

VAEGAN from "Autoencoding beyond pixels using a learned similarity metric" implemented in Pytorch. Clean, clear and with comments.

Official implementation of Paper Future Frame Prediction Using Convolutional VRNN for Anomaly Detection, AVSS 2019

Pytorch implementation for the paper: Data augmentation with norm-AE and selective pseudo-labelling for unsupervised domain adaptation

ECGAN is a research project for ECG data generation and abnormalty detection (morphologies as well as arrhythmias).

[TPAMI 2023] Generative Multi-Label Zero-Shot Learning

This is the corresponding repository of paper Limited Data Rolling Bearing Fault Diagnosis with Few-shot Learning

Official implementation of CVPR2023 paper "Bi-directional distribution alignment for transductive zero-shot learning""

Implementations of a number of generative models in Tensorflow 2. GAN, VAE, Seq2Seq, VAEGAN, GAIA, Spectrogram Inversion. Everything is self contained in a jupyter notebook for easy export to colab.

CVPR2022, BatchFormer: Learning to Explore Sample Relationships for Robust Representation Learning, https://arxiv.org/abs/2203.01522

LiveBot: Generating Live Video Comments Based on Visual and Textual Contexts (AAAI 2019)

A simple tutorial of Variational AutoEncoders with Pytorch

A Collection of Variational Autoencoders (VAE) in PyTorch.

Code for "Generative Oversampling for Imbalanced Data via Majority-Guided VAE", AISTATS2023.

This is the official implementation for paper Sentiment-oriented Transformer-based Variational Autoencoder Network for Live Video Commenting.

Proper implementation of ResNet-s for CIFAR10/100 in pytorch that matches description of the original paper.

Exemplar VAE: Linking Generative Models, Nearest Neighbor Retrieval, and Data Augmentation

Source code for AAAI 2024 paper: Compositional Generalization for Multi-Label Text Classification: A Data-Augmentation Approach

Chiller Fault Diagnosis based on VAE Enabled Generative Adversarial Networks