109 Open source projects that are alternatives of or similar to Imbalanced Semi Self

Enhancing the BERT training with Semi-supervised Generative Adversarial Networks

PyTorch implementation of EMAN for self-supervised and semi-supervised learning: https://arxiv.org/abs/2101.08482

Enhancing the BERT training with Semi-supervised Generative Adversarial Networks in Pytorch/HuggingFace

EC-GAN: Low-Sample Classification using Semi-Supervised Algorithms and GANs (AAAI 2021)

Deep Metric Transfer for Label Propagation with Limited Annotated Data

Code accompanying the paper "Semi-supervised adversarial audio source separation applied to singing voice extraction"

Pytorch Implementation of HybridNet: Classification and Reconstruction Cooperation for Semi-Supervised Learning (https://arxiv.org/abs/1807.11407)

An implementation for our paper: CsiGAN: Robust Channel State Information-based Activity Recognition with GANs (IEEE Internet of Things Journal, 2019), which is the semi-supervised Generative Adversarial Network (GAN) for Channel State Information (CSI) -based activity recognition.

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.

Source code and data for ACL 2019 Long Paper ``Semantic Parsing with Dual Learning".

Experiments on Flood Segmentation on Sentinel-1 SAR Imagery with Cyclical Pseudo Labeling and Noisy Student Training

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

[CVPR21] Implementation of our work "Three Ways to Improve Semantic Segmentation with Self-Supervised Depth Estimation"

Pytorch implementations of generative models: VQVAE2, AIR, DRAW, InfoGAN, DCGAN, SSVAE

Implementation of our paper "DMT: Dynamic Mutual Training for Semi-Supervised Learning"

PyTorch Implementation of ByteDance's Cross-speaker Emotion Transfer Based on Speaker Condition Layer Normalization and Semi-Supervised Training in Text-To-Speech

Semi-supervised Semantic Segmentation with Directional Context-aware Consistency (CVPR 2021)

Invariant representation learning from imaging and spectral data

Learning to Cluster. A deep clustering strategy.

Code for the paper: "SimPLE: Similar Pseudo Label Exploitation for Semi-Supervised Classification"

Semi-Supervised Learning and Collective Classification

Keras implementation of temporal ensembling(semi-supervised learning)

Unsupervised and Semi-supervised Learning with Categorical Generative Adversarial Networks

Python codes for weakly-supervised learning

Joint Semi-supervised Learning of Image Registration and Segmentation

PyProphet: Semi-supervised learning and scoring of OpenSWATH results.

Active learning for deep object detection using YOLO

Pseudo-Label: Semi-Supervised Learning on CIFAR-10 in Keras

Tensorflow Implementation on Paper [ECCV2018]Semi-Supervised Deep Learning with Memory

Implement of DiGCN, NeurIPS-2020

Semisupervided LDA for theory-driven text analysis

SPEAR: Programmatically label and build training data quickly.

TensorFlow implementation for "Guided Optical Flow Learning"

Unofficial PyTorch implementation of "FixMatch: Simplifying Semi-Supervised Learning with Consistency and Confidence"

This project is a semi-supervised approach to detect emotions on faces in-the-wild using GAN

Code for the paper Semi-Conditional Normalizing Flows for Semi-Supervised Learning

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

Official code for "Self-Supervised driven Consistency Training for Annotation Efficient Histopathology Image Analysis" Published in Medical Image Analysis (MedIA) Journal, Oct, 2021.

supervised and semi-supervised image classification with self-supervision (Keras)

Semi-Supervised Semantic Segmentation via Adaptive Equalization Learning, NeurIPS 2021 (Spotlight)

Generalized Product Quantization Network For Semi-supervised Image Retrieval - CVPR 2020

Tasks Assessing Protein Embeddings (TAPE), a set of five biologically relevant semi-supervised learning tasks spread across different domains of protein biology.

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

Source code of the KDD19 paper "Deep anomaly detection with deviation networks", weakly/partially supervised anomaly detection, few-shot anomaly detection

Tasks Assessing Protein Embeddings (TAPE), a set of five biologically relevant semi-supervised learning tasks spread across different domains of protein biology. (DEPRECATED)

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

🧹 Formerly for binary classification with noisy labels. Replaced by cleanlab.

Semi-supervised Learning GAN

Reproduce some methods in semi-supervised papers.

A full pipeline AutoML tool for tabular data

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

JCLAL is a general purpose framework developed in Java for Active Learning.

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

90%+ with 40 labels. please see the readme for details.

Benchmarks for semi-supervised domain generalization.

Semi Supervised Learning for Medical Image Segmentation, a collection of literature reviews and code implementations.

Tensorflow implementation of our paper: Few-shot 3D Multi-modal Medical Image Segmentation using Generative Adversarial Learning

code for our TPAMI 2021 paper "Source Data-absent Unsupervised Domain Adaptation through Hypothesis Transfer and Labeling Transfer"

noisy labels; missing labels; semi-supervised learning; entropy; uncertainty; robustness and generalisation.

Code for Paper ''Dual Student: Breaking the Limits of the Teacher in Semi-Supervised Learning'' [ICCV 2019]