1263 Repositories
Python latent-variable-models Libraries
A Transformer Implementation that is easy to understand and customizable.
Simple Transformer I've written a series of articles on the transformer architecture and language models on Medium. This repository contains an implem
Interpolation-based reduced-order models
Interpolation-reduced-order-models Interpolation-based reduced-order models High-fidelity computational fluid dynamics (CFD) solutions are time consum
Pytorch implementations of the paper Value Functions Factorization with Latent State Information Sharing in Decentralized Multi-Agent Policy Gradients
LSF-SAC Pytorch implementations of the paper Value Functions Factorization with Latent State Information Sharing in Decentralized Multi-Agent Policy G
Reference models and tools for Cloud TPUs.
Cloud TPUs This repository is a collection of reference models and tools used with Cloud TPUs. The fastest way to get started training a model on a Cl
This package implements the algorithms introduced in Smucler, Sapienza, and Rotnitzky (2020) to compute optimal adjustment sets in causal graphical models.
optimaladj: A library for computing optimal adjustment sets in causal graphical models This package implements the algorithms introduced in Smucler, S
for a paper about leveraging discourse markers for training new models
TSLM-DISCOURSE-MARKERS Scope This repository contains: (1) Code to extract discourse markers from wikipedia (TSA). (1) Code to extract significant dis
HuSpaCy: industrial-strength Hungarian natural language processing
HuSpaCy: Industrial-strength Hungarian NLP HuSpaCy is a spaCy model and a library providing industrial-strength Hungarian language processing faciliti
Repository for the AugmentedPCA Python package.
Overview This Python package provides implementations of Augmented Principal Component Analysis (AugmentedPCA) - a family of linear factor models that
Specification language for generating Generalized Linear Models (with or without mixed effects) from conceptual models
tisane Tisane: Authoring Statistical Models via Formal Reasoning from Conceptual and Data Relationships TL;DR: Analysts can use Tisane to author gener
A framework for multi-step probabilistic time-series/demand forecasting models
JointDemandForecasting.py A framework for multi-step probabilistic time-series/demand forecasting models File stucture JointDemandForecasting contains
Exploration of BERT-based models on twitter sentiment classifications
twitter-sentiment-analysis Explore the relationship between twitter sentiment of Tesla and its stock price/return. Explore the effect of different BER
PyTorch implementation(s) of various ResNet models from Twitch streams.
pytorch-resnet-twitch PyTorch implementation(s) of various ResNet models from Twitch streams. Status: ResNet50 currently not working. Will update in n
A minimal yet resourceful implementation of diffusion models (along with pretrained models + synthetic images for nine datasets)
A minimal yet resourceful implementation of diffusion models (along with pretrained models + synthetic images for nine datasets)
Machine learning and Deep learning models, deploy on telegram (the best social media)
Semi Intelligent BOT The project involves : Classifying fake news Classifying objects such as aeroplane, automobile, bird, cat, deer, dog, frog, horse
Script and models for clustering LAION-400m CLIP embeddings.
clustering-laion400m Script and models for clustering LAION-400m CLIP embeddings. Models were fit on the first million or so image embeddings. A subje
An executor that wraps 3D mesh models and encodes 3D content documents to d-dimension vector.
3D Mesh Encoder An Executor that receives Documents containing point sets data in its blob attribute, with shape (N, 3) and encodes it to embeddings o
Natural Language Processing Best Practices & Examples
NLP Best Practices In recent years, natural language processing (NLP) has seen quick growth in quality and usability, and this has helped to drive bus
Easy-to-use,Modular and Extendible package of deep-learning based CTR models .
DeepCTR DeepCTR is a Easy-to-use,Modular and Extendible package of deep-learning based CTR models along with lots of core components layers which can
Gathers machine learning and Tensorflow deep learning models for NLP problems, 1.13 Tensorflow 2.0
NLP-Models-Tensorflow, Gathers machine learning and tensorflow deep learning models for NLP problems, code simplify inside Jupyter Notebooks 100%. Tab
Implementation of deep learning models for time series in PyTorch.
List of Implementations: Currently, the reimplementation of the DeepAR paper(DeepAR: Probabilistic Forecasting with Autoregressive Recurrent Networks
Deep learning PyTorch library for time series forecasting, classification, and anomaly detection
Deep learning for time series forecasting Flow forecast is an open-source deep learning for time series forecasting framework. It provides all the lat
An API-first distributed deployment system of deep learning models using timeseries data to analyze and predict systems behaviour
Gordo Building thousands of models with timeseries data to monitor systems. Table of content About Examples Install Uninstall Developer manual How to
Cherche (search in French) allows you to create a neural search pipeline using retrievers and pre-trained language models as rankers.
Cherche (search in French) allows you to create a neural search pipeline using retrievers and pre-trained language models as rankers. Cherche is meant to be used with small to medium sized corpora. Cherche's main strength is its ability to build diverse and end-to-end pipelines.
Deepchecks is a Python package for comprehensively validating your machine learning models and data with minimal effort
Deepchecks is a Python package for comprehensively validating your machine learning models and data with minimal effort
List some popular DeepFake models e.g. DeepFake, FaceSwap-MarekKowal, IPGAN, FaceShifter, FaceSwap-Nirkin, FSGAN, SimSwap, CihaNet, etc.
deepfake-models List some popular DeepFake models e.g. DeepFake, CihaNet, SimSwap, FaceSwap-MarekKowal, IPGAN, FaceShifter, FaceSwap-Nirkin, FSGAN, Si
Beyond Accuracy: Behavioral Testing of NLP models with CheckList
CheckList This repository contains code for testing NLP Models as described in the following paper: Beyond Accuracy: Behavioral Testing of NLP models
🔅 Shapash makes Machine Learning models transparent and understandable by everyone
🎉 What's new ? Version New Feature Description Tutorial 1.6.x Explainability Quality Metrics To help increase confidence in explainability methods, y
List of papers, code and experiments using deep learning for time series forecasting
Deep Learning Time Series Forecasting List of state of the art papers focus on deep learning and resources, code and experiments using deep learning f
Not Suitable for Work (NSFW) classification using deep neural network Caffe models.
Open nsfw model This repo contains code for running Not Suitable for Work (NSFW) classification deep neural network Caffe models. Please refer our blo
Largest list of models for Core ML (for iOS 11+)
Since iOS 11, Apple released Core ML framework to help developers integrate machine learning models into applications. The official documentation We'v
Attention-based Transformation from Latent Features to Point Clouds (AAAI 2022)
Attention-based Transformation from Latent Features to Point Clouds This repository contains a PyTorch implementation of the paper: Attention-based Tr
Simulate genealogical trees and genomic sequence data using population genetic models
msprime msprime is a population genetics simulator based on tskit. Msprime can simulate random ancestral histories for a sample of individuals (consis
A Python Package For System Identification Using NARMAX Models
SysIdentPy is a Python module for System Identification using NARMAX models built on top of numpy and is distributed under the 3-Clause BSD license. N
Advbox is a toolbox to generate adversarial examples that fool neural networks in PaddlePaddle、PyTorch、Caffe2、MxNet、Keras、TensorFlow and Advbox can benchmark the robustness of machine learning models.
Advbox is a toolbox to generate adversarial examples that fool neural networks in PaddlePaddle、PyTorch、Caffe2、MxNet、Keras、TensorFlow and Advbox can benchmark the robustness of machine learning models. Advbox give a command line tool to generate adversarial examples with Zero-Coding.
StarGAN - Official PyTorch Implementation (CVPR 2018)
StarGAN: Unified Generative Adversarial Networks for Multi-Domain Image-to-Image Translation
Codes for "CSDI: Conditional Score-based Diffusion Models for Probabilistic Time Series Imputation"
CSDI This is the github repository for the NeurIPS 2021 paper "CSDI: Conditional Score-based Diffusion Models for Probabilistic Time Series Imputation
Reinforcement learning algorithms in RLlib
raylab Reinforcement learning algorithms in RLlib and PyTorch. Installation pip install raylab Quickstart Raylab provides agents and environments to b
Serve TensorFlow ML models with TF-Serving and then create a Streamlit UI to use them
TensorFlow Serving + Streamlit! ✨ 🖼️ Serve TensorFlow ML models with TF-Serving and then create a Streamlit UI to use them! This is a pretty simple S
Repository for Project Insight: NLP as a Service
Project Insight NLP as a Service Contents Introduction Features Installation Setup and Documentation Project Details Demonstration Directory Details H
Crowd sourced training data for Rasa NLU models
NLU Training Data Crowd-sourced training data for the development and testing of Rasa NLU models. If you're interested in grabbing some data feel free
An easy-to-use app to visualise attentions of various VQA models.
Ask Me Anything: A tool for visualising Visual Question Answering (AMA) An easy-to-use app to visualise attentions of various VQA models. Please click
An image classification app boilerplate to serve your deep learning models asap!
Image 🖼 Classification App Boilerplate Have you been puzzled by tons of videos, blogs and other resources on the internet and don't know where and ho
This MVP data web app uses the Streamlit framework and Facebook's Prophet forecasting package to generate a dynamic forecast from your own data.
📈 Automated Time Series Forecasting Background: This MVP data web app uses the Streamlit framework and Facebook's Prophet forecasting package to gene
Machine learning library for fast and efficient Gaussian mixture models
This repository contains code which implements the Stochastic Gaussian Mixture Model (S-GMM) for event-based datasets Dependencies CMake Premake4 Blaz
Code, pre-trained models and saliency results for the paper "Boosting RGB-D Saliency Detection by Leveraging Unlabeled RGB Images".
Boosting RGB-D Saliency Detection by Leveraging Unlabeled RGB This repository is the official implementation of the paper. Our results comming soon in
CV backbones including GhostNet, TinyNet and TNT, developed by Huawei Noah's Ark Lab.
CV Backbones including GhostNet, TinyNet, TNT (Transformer in Transformer) developed by Huawei Noah's Ark Lab. GhostNet Code TinyNet Code TNT Code Pyr
Official Pytorch Implementation for Splicing ViT Features for Semantic Appearance Transfer presenting Splice
Splicing ViT Features for Semantic Appearance Transfer [Project Page] Splice is a method for semantic appearance transfer, as described in Splicing Vi
Using BERT-based models for toxic span detection
SemEval 2021 Task 5: Toxic Spans Detection: Task: Link to SemEval-2021: Task 5 Toxic Span Detection is https://competitions.codalab.org/competitions/2
N-gram models- Unsmoothed, Laplace, Deleted Interpolation
N-gram models- Unsmoothed, Laplace, Deleted Interpolation
StarGAN v2 - Official PyTorch Implementation (CVPR 2020)
StarGAN v2 - Official PyTorch Implementation StarGAN v2: Diverse Image Synthesis for Multiple Domains Yunjey Choi*, Youngjung Uh*, Jaejun Yoo*, Jung-W
HomoInterpGAN - Homomorphic Latent Space Interpolation for Unpaired Image-to-image Translation
HomoInterpGAN Homomorphic Latent Space Interpolation for Unpaired Image-to-image Translation (CVPR 2019, oral) Installation The implementation is base
PyTorch implementation of InstaGAN: Instance-aware Image-to-Image Translation
InstaGAN: Instance-aware Image-to-Image Translation Warning: This repo contains a model which has potential ethical concerns. Remark that the task of
PyTorch Implementation of Exploring Explicit Domain Supervision for Latent Space Disentanglement in Unpaired Image-to-Image Translation.
DosGAN-PyTorch PyTorch Implementation of Exploring Explicit Domain Supervision for Latent Space Disentanglement in Unpaired Image-to-Image Translation
Pytorch-diffusion - A basic PyTorch implementation of 'Denoising Diffusion Probabilistic Models'
PyTorch implementation of 'Denoising Diffusion Probabilistic Models' This reposi
LightningFSL: Pytorch-Lightning implementations of Few-Shot Learning models.
LightningFSL: Few-Shot Learning with Pytorch-Lightning In this repo, a number of pytorch-lightning implementations of FSL algorithms are provided, inc
CorrProxies - Optimizing Machine Learning Inference Queries with Correlative Proxy Models
CorrProxies - Optimizing Machine Learning Inference Queries with Correlative Proxy Models
Augmented CLIP - Training simple models to predict CLIP image embeddings from text embeddings, and vice versa.
Train aug_clip against laion400m-embeddings found here: https://laion.ai/laion-400-open-dataset/ - note that this used the base ViT-B/32 CLIP model. S
TrainingBike - Code, models and schematics I've used to interface my stationary training bike with PC.
TrainingBike Code, models and schematics I've used to interface my stationary training bike with PC. You can find more information about the project i
Implementation of hyperparameter optimization/tuning methods for machine learning & deep learning models
Hyperparameter Optimization of Machine Learning Algorithms This code provides a hyper-parameter optimization implementation for machine learning algor
A collection of Machine Learning Models To Web Api which are built on open source technologies/frameworks like Django, Flask.
Author Ibrahim Koné From-Machine-Learning-Models-To-WebAPI A collection of Machine Learning Models To Web Api which are built on open source technolog
Time-series-deep-learning - Developing Deep learning LSTM, BiLSTM models, and NeuralProphet for multi-step time-series forecasting of stock price.
Stock Price Prediction Using Deep Learning Univariate Time Series Predicting stock price using historical data of a company using Neural networks for
Flask app to predict daily radiation from the time series of Solcast from Islamabad, Pakistan
Solar-radiation-ISB-MLOps - Flask app to predict daily radiation from the time series of Solcast from Islamabad, Pakistan.
Minimal diffusion models - Minimal code and simple experiments to play with Denoising Diffusion Probabilistic Models (DDPMs)
Minimal code and simple experiments to play with Denoising Diffusion Probabilist
SOTA easy to use PyTorch-based DL training library
Easily train or fine-tune SOTA computer vision models from one training repository. SuperGradients Introduction Welcome to SuperGradients, a free open
Code for Universal Semi-Supervised Semantic Segmentation models paper accepted in ICCV 2019
USSS_ICCV19 Code for Universal Semi Supervised Semantic Segmentation accepted to ICCV 2019. Full Paper available at https://arxiv.org/abs/1811.10323.
A Probabilistic End-To-End Task-Oriented Dialog Model with Latent Belief States towards Semi-Supervised Learning
LABES This is the code for EMNLP 2020 paper "A Probabilistic End-To-End Task-Oriented Dialog Model with Latent Belief States towards Semi-Supervised L
Training neural models with structured signals.
Neural Structured Learning in TensorFlow Neural Structured Learning (NSL) is a new learning paradigm to train neural networks by leveraging structured
Ecco is a python library for exploring and explaining Natural Language Processing models using interactive visualizations.
Visualize, analyze, and explore NLP language models. Ecco creates interactive visualizations directly in Jupyter notebooks explaining the behavior of Transformer-based language models (like GPT2, BERT, RoBERTA, T5, and T0).
Beibo is a Python library that uses several AI prediction models to predict stocks returns over a defined period of time.
Beibo is a Python library that uses several AI prediction models to predict stocks returns over a defined period of time.
Contrastive Learning of Structured World Models
Contrastive Learning of Structured World Models This repository contains the official PyTorch implementation of: Contrastive Learning of Structured Wo
Variable Transformer Calculator
✠ VASCO - VAriable tranSformer CalculatOr Software que calcula informações de transformadores feita para a matéria de "Conversão Eletromecânica de Ene
Official release of MSHT: Multi-stage Hybrid Transformer for the ROSE Image Analysis of Pancreatic Cancer axriv: http://arxiv.org/abs/2112.13513
MSHT: Multi-stage Hybrid Transformer for the ROSE Image Analysis This is the official page of the MSHT with its experimental script and records. We de
Quantized models with python
quantized-network download .pth files to qmodels/: googlenet : https://download.
A modular dynamical-systems model of Ethereum's validator economics.
CADLabs Ethereum Economic Model A modular dynamical-systems model of Ethereum's validator economics, based on the open-source Python library radCAD, a
Official repository of the paper Learning to Regress 3D Face Shape and Expression from an Image without 3D Supervision
Official repository of the paper Learning to Regress 3D Face Shape and Expression from an Image without 3D Supervision
GUI for visualization and interactive editing of SMPL-family body models ie. SMPL, SMPL-X, MANO, FLAME.
Body Model Visualizer Introduction This is a simple Open3D-based GUI for SMPL-family body models. This GUI lets you play with the shape, expression, a
GUI for visualization and interactive editing of SMPL-family body models ie. SMPL, SMPL-X, MANO, FLAME.
Body Model Visualizer Introduction This is a simple Open3D-based GUI for SMPL-family body models. This GUI lets you play with the shape, expression, a
LazyText is inspired b the idea of lazypredict, a library which helps build a lot of basic models without much code.
LazyText is inspired b the idea of lazypredict, a library which helps build a lot of basic models without much code. LazyText is for text what lazypredict is for numeric data.
Tools to convert SQLAlchemy models to Pydantic models
Pydantic-SQLAlchemy Tools to generate Pydantic models from SQLAlchemy models. Still experimental. How to use Quick example: from typing import List f
Implementation of the final project of the course DDA6309 Probabilistic Graphical Model
Task-aware Joint CWS and POS (TCwsPos) This is the implementation of the final project of the course DDA6309 Probabilistic Graphical Models, The Chine
CALPHAD tools for designing thermodynamic models, calculating phase diagrams and investigating phase equilibria.
CALPHAD tools for designing thermodynamic models, calculating phase diagrams and investigating phase equilibria.
A Python package to create, run, and post-process MODFLOW-based models.
Version 3.3.5 — release candidate Introduction FloPy includes support for MODFLOW 6, MODFLOW-2005, MODFLOW-NWT, MODFLOW-USG, and MODFLOW-2000. Other s
A minimal implementation of face-detection models using flask, gunicorn, nginx, docker, and docker-compose
Face-Detection-flask-gunicorn-nginx-docker This is a simple implementation of dockerized face-detection restful-API implemented with flask, Nginx, and
An executor that loads ONNX models and embeds documents using the ONNX runtime.
ONNXEncoder An executor that loads ONNX models and embeds documents using the ONNX runtime. Usage via Docker image (recommended) from jina import Flow
Model Zoo for MindSpore
Welcome to the Model Zoo for MindSpore In order to facilitate developers to enjoy the benefits of MindSpore framework, we will continue to add typical
A few stylization coreML models that I've trained with CreateML
CoreML-StyleTransfer A few stylization coreML models that I've trained with CreateML You can open and use the .mlmodel files in the "models" folder in
Latte: Cross-framework Python Package for Evaluation of Latent-based Generative Models
Cross-framework Python Package for Evaluation of Latent-based Generative Models Latte Latte (for LATent Tensor Evaluation) is a cross-framework Python
High-Resolution Image Synthesis with Latent Diffusion Models
Latent Diffusion Models arXiv | BibTeX High-Resolution Image Synthesis with Latent Diffusion Models Robin Rombach*, Andreas Blattmann*, Dominik Lorenz
YAML-formatted plain-text file based models for Flask backed by Flask-SQLAlchemy
Flask-FileAlchemy Flask-FileAlchemy is a Flask extension that lets you use Markdown or YAML formatted plain-text files as the main data store for your
Python SDK for building, training, and deploying ML models
Overview of Kubeflow Fairing Kubeflow Fairing is a Python package that streamlines the process of building, training, and deploying machine learning (
This repository contains the code needed to train Mega-NeRF models and generate the sparse voxel octrees
Mega-NeRF This repository contains the code needed to train Mega-NeRF models and generate the sparse voxel octrees used by the Mega-NeRF-Dynamic viewe
Source code of the paper "Deep Learning of Latent Variable Models for Industrial Process Monitoring".
Source code of the paper "Deep Learning of Latent Variable Models for Industrial Process Monitoring".
This repository contains the code, data, and models of the paper titled "CrossSum: Beyond English-Centric Cross-Lingual Abstractive Text Summarization for 1500+ Language Pairs".
CrossSum This repository contains the code, data, and models of the paper titled "CrossSum: Beyond English-Centric Cross-Lingual Abstractive Text Summ
Matching python environment code for Lux AI 2021 Kaggle competition, and a gym interface for RL models.
Lux AI 2021 python game engine and gym This is a replica of the Lux AI 2021 game ported directly over to python. It also sets up a classic Reinforceme
Official codebase for running the small, filtered-data GLIDE model from GLIDE: Towards Photorealistic Image Generation and Editing with Text-Guided Diffusion Models.
GLIDE This is the official codebase for running the small, filtered-data GLIDE model from GLIDE: Towards Photorealistic Image Generation and Editing w
High-Resolution Image Synthesis with Latent Diffusion Models
Latent Diffusion Models Requirements A suitable conda environment named ldm can be created and activated with: conda env create -f environment.yaml co
Quick tutorial on orchest.io that shows how to build multiple deep learning models on your data with a single line of code using python
Deep AutoViML Pipeline for orchest.io Quickstart Build Deep Learning models with a single line of code: deep_autoviml Deep AutoViML helps you build te
📜 GPT-2 Rhyming Limerick and Haiku models using data augmentation
Well-formed Limericks and Haikus with GPT2 📜 GPT-2 Rhyming Limerick and Haiku models using data augmentation In collaboration with Matthew Korahais &
PyTorch implementation for our AAAI 2022 Paper "Graph-wise Common Latent Factor Extraction for Unsupervised Graph Representation Learning"
deepGCFX PyTorch implementation for our AAAI 2022 Paper "Graph-wise Common Latent Factor Extraction for Unsupervised Graph Representation Learning" Pr