321 Open source projects that are alternatives of or similar to SimPLE

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.

Learning to Cluster. A deep clustering strategy.

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

Federated Learning Library: https://fedml.ai

Implementation of a Neural Network that can detect whether a video is in-game or not

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

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

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

✂️ Automated high-quality background removal framework for an image using neural networks. ✂️

Python codes for weakly-supervised learning

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

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

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

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

Transfer Learning with DCNNs (DenseNet, Inception V3, Inception-ResNet V2, VGG16) for skin lesions classification

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

Address book for computer vision models.

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

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.

A collection of projects which explore image classification on chest x-ray images (via the NIH dataset)

Weakly- and Semi-Supervised Panoptic Segmentation (ECCV18)

Unsupervised Data Augmentation (UDA)

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

Dialogue Knowledge Transfer Networks (DiKTNet)

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

Code for Adversarial Training Methods for Semi-Supervised Text Classification

Tensorflow source code for "CleanNet: Transfer Learning for Scalable Image Classifier Training with Label Noise" (CVPR 2018)

Deep Metric Transfer for Label Propagation with Limited Annotated Data

Active learning for deep object detection using YOLO

Implementation of ULMFit algorithm for text classification via transfer learning

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

Repositório dos exemplos e desafios utilizados na disciplina de Visão Computacional do curso de MBA Machine Learning da FIAP

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

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

Tensorflow implementation of Adversarial Autoencoders

Unseen Object Segmentation in Videos via Transferable Representations, ACCV 2018 (oral)

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

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

VOSK Speech Recognition Toolkit

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

resource collection for transfer learning!

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

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

🤖 Cozmo the Robot recognizes objects with TensorFlow

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

tensorflow object detection api helper tool ( custom object detection )

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

Building an ACL tear detector to spot knee injuries from MRIs with PyTorch (MRNet)

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

A Simple but Powerful CNN Trainer For PyTorch

Code for reproducing ICT ( published in IJCAI 2019)

Knowledge-Aware machine LEarning (KALE): accessible machine learning from multiple sources for interdisciplinary research, part of the 🔥PyTorch ecosystem

Keras implementation of temporal ensembling(semi-supervised learning)

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

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

Pytorch implementation of Virtual Adversarial Training

Pytorch implementation of "Graph Convolutional Networks for Text Classification"

Face Recognition with Transfer Learning

Customisable Unified Physical Simulations (CUPS) for Reinforcement Learning. Experiments run on the ai2thor environment (http://ai2thor.allenai.org/) e.g. using A3C, RainbowDQN and A3C_GA (Gated Attention multi-modal fusion) for Task-Oriented Language Grounding (tasks specified by natural language instructions) e.g. "Pick up the Cup or else"

Real-time AI-powered translation of American sign language to text