Search Packages

alibi-detect

Algorithms for outlier, adversarial and drift detection

otx

Train, Evaluate, Optimize, Deploy Computer Vision Models via OpenVINO™

accelbrainbeat

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.

adbench

Official Implement of "ADBench: Anomaly Detection Benchmark", NeurIPS 2022.

tape-proteins

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

rul-datasets

A collection of datasets for RUL estimation as Lightning Data Modules.

pydbm

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.

semilearn

A Unified Semi-Supervised Learning Codebase (NeurIPS'22)

pysummarization

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.

pyqlearning

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.

pytorch-partial-tagger

Sequence Tagger for Partially Annotated Dataset in PyTorch

susi

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

modssc

ModSSC: A Modular Framework for Semi Supervised Classification

bio-embeddings-tape-proteins

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

hypergbm

A full pipeline AutoML tool for tabular data

disc

A highly scalable and accurate inference of gene expression and structure for single-cell transcriptomes using semi-supervised deep learning.

visagesnap

Easy-to-Use library to recognize faces, train the model, provide predictions

accel-brain-base

accel-brain-base is a basic library of the Deep Learning for rapid development at low cost. This library makes it possible to design and implement deep learning, which must be configured as a complex system, by combining a plurality of functionally differentiated modules such as a Deep Boltzmann Machines(DBMs), an Auto-Encoder, an Encoder/Decoder based on Long Short-Term Memory(LSTM), a Convolutional Auto-Encoder(CAE), and Transformer.

keras-unsupervised

Keras framework for unsupervised learning

pygan

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.

sslearn

The sslearn library is a Python package for machine learning over Semi-supervised datasets. It is an extension of scikit-learn.

ssl-dnx

TFG - Semisupervised learning and instance selection methods

lamda-ssl

30 Semi-Supervised Learning Algorithms

torchwisdom

High level API for training deep learning model in PyTorch