235 Open source projects that are alternatives of or similar to semantic-parsing-dual

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

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

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

Awesome Graph Self-Supervised Learning

TKDE 22. CCCL: Contrastive Cascade Graph Learning.

Invariant representation learning from imaging and spectral data

AAAI'21: Data Augmentation for Graph Neural Networks

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

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

An extended TSP (Time Stretched Pulse). CAPRICEP substantially replaces FVN. CAPRICEP enables interactive and real-time measurement of the linear time-invariant, the non-linear time-invariant, and random and time varying responses simultaneously.

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

Reproduce some methods in semi-supervised papers.

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

Audio degradation toolbox in python, with a command-line tool. It is useful to apply controlled degradations to audio: e.g. data augmentation, evaluation in noisy conditions, etc.

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

Multiclass image classification using Convolutional Neural Network

Text-to-SQL in the Wild: A Naturally-Occurring Dataset Based on Stack Exchange Data

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

GAP-text2SQL: Learning Contextual Representations for Semantic Parsing with Generation-Augmented Pre-Training

3D augmentation and transforms of 2D/3D sparse data, such as 3D triangle meshes or point clouds in Euclidean space. Extension of the Fast.ai library to train Sub-manifold Sparse Convolution Networks

our code for paper 'PointCutMix: Regularization Strategy for Point Cloud Classification'

Enhancing the BERT training with Semi-supervised Generative Adversarial Networks

Image rotation and cropping out the black borders in TensorFlow

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

[Medical Image Analysis] Adversarial Data Augmentation with Chained Transformations (AdvChain)

Programming assignments and quizzes from all courses within the GANs specialization offered by deeplearning.ai

A generalizable application framework for segmentation, regression, and classification using PyTorch

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

Multiple paper open-source codes of the Microsoft Research Asia DKI group

[ICCV 2021] Excavating the Potential Capacity of Self-Supervised Monocular Depth Estimation

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

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

Semisupervided LDA for theory-driven text analysis

A tensorflow implementation of neural sequence-to-sequence parser for converting natural language queries to logical form.

Translating natural language questions to a structured query language

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

Tensorflow implementation of the Manifold Mixup machine learning research paper

Implementation of experiments in paper "Learning from Rules Generalizing Labeled Exemplars" to appear in ICLR2020 (https://openreview.net/forum?id=SkeuexBtDr)

Library for data augmentation

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.

KitanaQA: Adversarial training and data augmentation for neural question-answering models

🌶️ R²SQL: "Dynamic Hybrid Relation Network for Cross-Domain Context-Dependent Semantic Parsing." (AAAI 2021)

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

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

TensorFlow implementation for "Guided Optical Flow Learning"

SnapMix: Semantically Proportional Mixing for Augmenting Fine-grained Data (AAAI 2021)

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

Keras implementation of temporal ensembling(semi-supervised learning)

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

Tensor2tensor experiment with SpecAugment

Benchmarks for semi-supervised domain generalization.

Deep Metric Transfer for Label Propagation with Limited Annotated Data

PyTorch port of the paper "Language to Logical Form with Neural Attention"

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

[SemEval'19] Code for "HLT@SUDA at SemEval 2019 Task 1: UCCA Graph Parsing as Constituent Tree Parsing"

Python codes for weakly-supervised learning

Light-weight Single Person Pose Estimator

A curated list of papers, code and resources pertaining to few-shot image generation.

Joint Semi-supervised Learning of Image Registration and Segmentation

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