689 Open source projects that are alternatives of or similar to metric-transfer.pytorch

Learning to Cluster. A deep clustering strategy.

MARTA GANs: Unsupervised Representation Learning for Remote Sensing Image Classification

SPEAR: Programmatically label and build training data quickly.

Sinkhorn Label Allocation is a label assignment method for semi-supervised self-training algorithms. The SLA algorithm is described in full in this ICML 2021 paper: https://arxiv.org/abs/2102.08622.

SCAN: Learning to Classify Images without Labels (ECCV 2020), incl. SimCLR.

Unsupervised and Semi-supervised Learning with Categorical Generative Adversarial Networks

Implementing Billion-scale semi-supervised learning for image classification using Pytorch

Machine Learning (EE 5184) in NTU

TensorFlow implementation for "Guided Optical Flow Learning"

Official PyTorch code for CVPR 2020 paper "Deep Active Learning for Biased Datasets via Fisher Kernel Self-Supervision"

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

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

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

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

Official Repository of "Contextual Graph Markov Model" (ICML 2018 - JMLR 2020)

Pre-trained VGG-Net Model for image classification using tensorflow

[ICCVW 2021] Rethinking Content and Style: Exploring Bias for Unsupervised Disentanglement

📄 Spatial Contrastive Learning for Few-Shot Classification (ECML/PKDD 2021).

Balanced Multiclass Image Classification with TensorFlow on Python.

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

Active learning for deep object detection using YOLO

Pytorch implementation of pyramidnet

image classifier, retrained for specific classes

[ICCV 2019 Oral] TA3N: https://github.com/cmhungsteve/TA3N (Most updated repo)

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

UI for Keras to implement image classification written in python and django

Python codes for weakly-supervised learning

Main component extraction for outlier detection

Tensorflow implementation of Adversarial Autoencoders

Real time image classification with React Native and Tensorflow lite.

machine learning algorithms in Swift

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

Code release for "Learning Shape Abstractions by Assembling Volumetric Primitives " (CVPR 2017)

This is an official implementation for "SimMIM: A Simple Framework for Masked Image Modeling".

PyTorch implementation of shake-drop regularization

Traffic Sign Recognition with Keras.

Experiments on unsupervised point cloud reconstruction.

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

official implemntation for "Contrastive Learning with Stronger Augmentations"

An unsupervised Chinese word segmentation tool.

Scripts for training an AI to play the endless runner Subway Surfers using a supervised machine learning approach by imitation and a convolutional neural network (CNN) for image classification

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

Video Representation Learning by Recognizing Temporal Transformations. In ECCV, 2020.

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

TOD: GPU-accelerated Outlier Detection via Tensor Operations

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

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

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

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

Unsupervised Learning to Market Behavior Forecasting Example

Unsupervised machine learning Principal Component Analysis (PCA) on the Dow Jones Industrial Average index and it's respective 30 stocks to construct an optimized diversified intelligent portfolio.

VOSK Speech Recognition Toolkit

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

[IEEE Access] "Head Network Distillation: Splitting Distilled Deep Neural Networks for Resource-constrained Edge Computing Systems" and [ACM MobiCom HotEdgeVideo 2019] "Distilled Split Deep Neural Networks for Edge-assisted Real-time Systems"

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

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.

Revisiting Contrastive Methods for Unsupervised Learning of Visual Representations. [NeurIPS 2021]

MyBB CAPTCHA Solver using Convolutional Neural Network in Keras

Template-Based Question Generation from Retrieved Sentences for Improved Unsupervised Question Answering

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