169 Open source projects that are alternatives of or similar to temporal-ensembling-semi-supervised

Pytorch implementation of Virtual Adversarial Training

PyTorch implementation of Adversarially Learned Inference (BiGAN).

Implementation of Temporal Ensembling for Semi-Supervised Learning by Laine et al. with tensorflow eager execution

Protein-compound affinity prediction through unified RNN-CNN

Pytorch implementation of "Graph Convolutional Networks for Text Classification"

VOSK Speech Recognition Toolkit

[CVPR 2021] DeFMO: Deblurring and Shape Recovery of Fast Moving Objects

Pytorch implementation of Conditional Image Synthesis with Auxiliary Classifier GANs

A PyTorch implementation of Deep SAD, a deep Semi-supervised Anomaly Detection method.

SuSi: Python package for unsupervised, supervised and semi-supervised self-organizing maps (SOM)

Implementations of various VAE-based semi-supervised and generative models in PyTorch

Official PyTorch implementation of "Towards Deeper Graph Neural Networks" [KDD2020]

Autoencoders for Link Prediction and Semi-Supervised Node Classification (DSAA 2018)

Semi-supervised Medical Image Segmentation through Dual-task Consistency

Reimplementation of "Realistic Evaluation of Deep Semi-Supervised Learning Algorithms"

A state-of-the-art semi-supervised method for image recognition

[ICCV 2019]Aggregation via Separation: Boosting Facial Landmark Detector with Semi-Supervised Style Transition

Several SSL methods (Pi model, Mean Teacher) are implemented in pytorch

Python codes for weakly-supervised learning

Companion repository to GANs in Action: Deep learning with Generative Adversarial Networks

Pytorch Implementation of "Adversarial Learning For Semi-Supervised Semantic Segmentation" for ICLR 2018 Reproducibility Challenge

PseudoLabel 2013, VAT, PI model, Tempens, MeanTeacher, ICT, MixMatch, FixMatch

GANomaly: Semi-Supervised Anomaly Detection via Adversarial Training

Implementation with some extensions of the paper "Snowball: Extracting Relations from Large Plain-Text Collections" (Agichtein and Gravano, 2000)

📜 An up-to-date & curated list of awesome semi-supervised learning papers, methods & resources.

Code for the paper STN-OCR: A single Neural Network for Text Detection and Text Recognition

speech to text with self-supervised learning based on wav2vec 2.0 framework

See Triple-GAN-V2 in PyTorch: https://github.com/taufikxu/Triple-GAN

Pytorch Implementation of the paper MixMatch: A Holistic Approach to Semi-Supervised Learning (https://arxiv.org/pdf/1905.02249.pdf)

Code for "MixMatch - A Holistic Approach to Semi-Supervised Learning"

[CVPR 2022] ST++: Make Self-training Work Better for Semi-supervised Semantic Segmentation

NeurIPS 2019: HyperGCN: A New Method of Training Graph Convolutional Networks on Hypergraphs

A curated collection of adversarial attack and defense on graph data.

Source code and dataset of the NeurIPS 2020 paper "Graph Random Neural Network for Semi-Supervised Learning on Graphs"

Implementation of the KDD 2020 paper "Graph Structure Learning for Robust Graph Neural Networks"

Code for paper "Sparsely Grouped Multi-task Generative Adversarial Networks for Facial Attribute Manipulation"

[CVPR 2020] Semi-Supervised Semantic Segmentation with Cross-Consistency Training.

Active learning for deep object detection using YOLO

Code for Universal Semi-Supervised Semantic Segmentation models paper accepted in ICCV 2019

The purpose of this repository is to make prototypes as case study in the context of proof of concept(PoC) and research and development(R&D) that I have written in my website. The main research topics are Auto-Encoders in relation to the representation learning, the statistical machine learning for energy-based models, adversarial generation networks(GANs), Deep Reinforcement Learning such as Deep Q-Networks, semi-supervised learning, and neural network language model for natural language processing.

😔 😞 😣 😖 😩 Detect depression on social media using the ssToT method introduced in our ASONAM 2017 paper titled "Semi-Supervised Approach to Monitoring Clinical Depressive Symptoms in Social Media"

Reproduce some methods in semi-supervised papers.

Implementation of Ladder Network in PyTorch.

Weakly- and Semi-Supervised Panoptic Segmentation (ECCV18)

Federated Learning Library: https://fedml.ai

I try my best to keep updated cutting-edge knowledge in Machine Learning/Deep Learning and Natural Language Processing. These are my notes on some good papers

Algorithms for outlier and adversarial instance detection, concept drift and metrics.

Unsupervised Data Augmentation (UDA)

Code for the AAAI 2018 publication "SEE: Towards Semi-Supervised End-to-End Scene Text Recognition"

PyTorch implementation of shake-drop regularization

A Tensorflow implementation of Semi-supervised Learning Generative Adversarial Networks (NIPS 2016: Improved Techniques for Training GANs).

The standard package for machine learning with noisy labels, finding mislabeled data, and uncertainty quantification. Works with most datasets and models.

Adversarial Learning for Semi-supervised Semantic Segmentation, BMVC 2018

Semi-supervised GAN in "Improved Techniques for Training GANs"

[NeurIPS 2020] Semi-Supervision (Unlabeled Data) & Self-Supervision Improve Class-Imbalanced / Long-Tailed Learning

Code for Adversarial Training Methods for Semi-Supervised Text Classification

A Gluon implement of Residual Attention Network. Best acc on cifar10-97.78%.

Deep Metric Transfer for Label Propagation with Limited Annotated Data

Implementation of Conv-based and Vit-based networks designed for CIFAR.

Tensorflow implementation of Adversarial Autoencoders