Reverse Dependencies of pytorch-ignite
The following projects have a declared dependency on pytorch-ignite:
- active-transformers — Active Learning for Transformer with focus on Sequence Tagging tasks
- atombench — atombench
- atomvision — atomvision
- autoembedder — PyTorch autoencoder with additional embeddings layer for categorical data.
- azureml-automl-dnn-vision — AutoML DNN Vision Models
- azureml-contrib-automl-dnn-vision — AutoML DNN Vision Models
- blackhc.project — Notebook setup code
- catbird — Paraphrase generation Toolbox and Benchmark
- chady — A package for ML libraries
- chatting-chatbots — A library for running experiments of multiple chatbots having conversations with each other.
- dasheng — no summary
- decofre — Neural coreference resolution
- deepchecks — Package for validating your machine learning model and data
- democlassi — Collection of my python functions for training pytorch models to classify emotion, age, race, gender
- draupnir — Ancestral sequence reconstruction using a tree structured Ornstein Uhlenbeck variational autoencoder
- eir-dl — Deep learning framework for genomics and multi-modal data
- EMCqMRI — A distribution of a general tool for training and inference of QMRI models
- fastai — fastai simplifies training fast and accurate neural nets using modern best practices
- fastAIcourse — fastAIcourse
- fedbiomed-cli — no summary
- fibad — no summary
- Fireworks-ml — A batch-processing framework for data analysis and machine learning using PyTorch.
- geyser-lava — Compose and execute python objects
- gleipnir-tcr — Gleipnir
- gravitorch — A library to train ML models with PyTorch
- ignite-simple — Easily train pytorch models with automatic LR and BS tuning
- igniter — no summary
- ImputeHiFI — no summary
- karbonn — A library of PyTorch modules
- libcrap — Crappy functions Crabman uses. Some helpers for pytorch and ignite.
- melmac — A package for neural multilabel and multiclass classification.
- ml-workflow — Pytorch project template and required tools
- monai — AI Toolkit for Healthcare Imaging
- monai-weekly — AI Toolkit for Healthcare Imaging
- mpdd-alignn — A version of the NIST-JARVIS ALIGNN optimized in terms of model performance and to some extent reliability, for large-scale deployments over the MPDD infrastructure by Phases Research Lab.
- neural-semigroups — Neural networks powered research of semigroups
- newAI — newAi
- nfflr — neural force field learning toolkit
- niiv — Self-Supervised Neural Implicit Isotropic Volume Reconstruction
- novas3d — no summary
- nurphy — A deep learning based natural language understanding module
- nussl — A flexible sound source separation library.
- optuna-integration — Integration libraries of Optuna.
- phlower — This is a Python package which helps you handle GNN especially for physics problems.
- pipelinex — PipelineX: Python package to build ML pipelines for experimentation with Kedro, MLflow, and more
- ptan — PyTorch reinforcement learning framework
- pyklopp — no summary
- pysiml — SiML - a Simulation ML library
- pytorch-adapt — Domain adaptation made easy. Fully featured, modular, and customizable.
- pytorch-flame — A library based on Ignite to help you train and evaluate PyTorch neural networks more easily.
- pytorch-hrvvi-ext — HrvvI's extension to PyTorch
- pytorch-igniter — Simplify running pytorch training with fully-configured pytorch-ignite
- pytorch-light — Light.
- pytorch-tao — A toolbox for a specific Machine Learning training project
- quartic-sdk — QuarticSDK is the SDK package which exposes the APIs to the user
- quartic-sdk-gsk — QuarticSDK is the SDK package which exposes the APIs to the user
- runml-checks — Package for validating your machine learning model and data
- sccross — Single cell multi-omics cross modal generation, multi-omics simulation and perturbation
- scglue — Graph-linked unified embedding for unpaired single-cell multi-omics data integration
- socialED — A Python Library for Social Event Detection
- stVAE — Style transfer variational autoencoder
- texi — Text processing toolbox.
- thermostat-datasets — Collection of NLP model explanations and accompanying analysis tools
- TimeSeriesML — TimeSeriesML
- torch-optim — PyTorch models optimization using neural network pruning
- traintool — Machine learning in one line of code
- upside-down-rl — no summary
- uwnet — PyTorch training code for climate modeling
- vegvisir — Vegvisir
- waterch-tasker — A scalable and extendable experiment task scheduler framework.
- xares — eXtensive Audio Representation and Evaluation Suite
- yaib — Yet Another ICU Benchmark is a holistic framework for the automation of the development of clinical prediction models on ICU data. Users can create custom datasets, cohorts, prediction tasks, endpoints, and models.
- yonlu — A deep learning based natural language understanding module
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