1928 Repositories
Python Breast-Cancer-Classification-Model Libraries
A Python package to process & model ChEMBL data.
insilico: A Python package to process & model ChEMBL data. ChEMBL is a manually curated chemical database of bioactive molecules with drug-like proper
A python package to manage the stored receiver-side Strain Green's Tensor (SGT) database of 3D background models and able to generate Green's function and synthetic waveform
A python package to manage the stored receiver-side Strain Green's Tensor (SGT) database of 3D background models and able to generate Green's function and synthetic waveform
Supervised Classification from Text (P)
MSc-Thesis Module: Masters Research Thesis Language: Python Grade: 75 Title: An investigation of supervised classification of therapeutic process from
Code for Discovering Topics in Long-tailed Corpora with Causal Intervention.
Code for Discovering Topics in Long-tailed Corpora with Causal Intervention ACL2021 Findings Usage 0. Prepare environment Requirements: python==3.6 te
A single model for shaping, creating, accessing, storing data within a Database
'db' within pydantic - A single model for shaping, creating, accessing, storing data within a Database Key Features Integrated Redis Caching Support A
Image classification for projects and researches
This is a tool to help you quickly solve classification problems including: data analysis, training, report results and model explanation.
Repository for the electrical and ICT benchmark model developed in the ERIGrid 2.0 project.
Benchmark Model Electrical and ICT System This repository contains the documentation, code, and models for the electrical and ICT benchmark model deve
A large-image collection explorer and fast classification tool
IMAX: Interactive Multi-image Analysis eXplorer This is an interactive tool for visualize and classify multiple images at a time. It written in Python
Conditional Transformer Language Model for Controllable Generation
CTRL - A Conditional Transformer Language Model for Controllable Generation Authors: Nitish Shirish Keskar, Bryan McCann, Lav Varshney, Caiming Xiong,
A simple, fully convolutional model for real-time instance segmentation.
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Python scripts for performing lane detection using the LSTR model in ONNX
ONNX LSTR Lane Detection Python scripts for performing lane detection using the Lane Shape Prediction with Transformers (LSTR) model in ONNX. Requirem
Pytorch implementation of 'Fingerprint Presentation Attack Detector Using Global-Local Model'
RTK-PAD This is an official pytorch implementation of 'Fingerprint Presentation Attack Detector Using Global-Local Model', which is accepted by IEEE T
Source code and notebooks to reproduce experiments and benchmarks on Bias Faces in the Wild (BFW).
Face Recognition: Too Bias, or Not Too Bias? Robinson, Joseph P., Gennady Livitz, Yann Henon, Can Qin, Yun Fu, and Samson Timoner. "Face recognition:
using STGCN to achieve egg classification task
EEG Classification The task requires us to classify electroencephalography(EEG) into six categories, including human body, human face, animal body,
Python implementation of an automatic parallel parking system in a virtual environment, including path planning, path tracking, and parallel parking
Automatic Parallel Parking: Path Planning, Path Tracking & Control This repository contains a python implementation of an automatic parallel parking s
Biterm Topic Model (BTM): modeling topics in short texts
Biterm Topic Model Bitermplus implements Biterm topic model for short texts introduced by Xiaohui Yan, Jiafeng Guo, Yanyan Lan, and Xueqi Cheng. Actua
Python package for covariance matrices manipulation and Biosignal classification with application in Brain Computer interface
pyRiemann pyRiemann is a python package for covariance matrices manipulation and classification through Riemannian geometry. The primary target is cla
Binary LSTM model for text classification
Text Classification The purpose of this repository is to create a neural network model of NLP with deep learning for binary classification of texts re
A machine learning model for analyzing text for user sentiment and determine whether its a positive, neutral, or negative review.
Sentiment Analysis on Yelp's Dataset Author: Roberto Sanchez, Talent Path: D1 Group Docker Deployment: Deployment of this application can be found her
This is a Machine Learning model which predicts the presence of Diabetes in Patients
Diabetes Disease Prediction This is a machine Learning mode which tries to determine if a person has a diabetes or not. Data The dataset is in comma s
PyExplainer: A Local Rule-Based Model-Agnostic Technique (Explainable AI)
PyExplainer PyExplainer is a local rule-based model-agnostic technique for generating explanations (i.e., why a commit is predicted as defective) of J
An interactive dashboard for visualisation, integration and classification of data using Active Learning.
AstronomicAL An interactive dashboard for visualisation, integration and classification of data using Active Learning. AstronomicAL is a human-in-the-
This repository will help you get label for images in Stanford Cars Dataset.
STANFORD CARS DATASET stanford-cars "The Cars dataset contains 16,185 images of 196 classes of cars. The data is split into 8,144 training images and
This project uses unsupervised machine learning to identify correlations between daily inoculation rates in the USA and twitter sentiment in regards to COVID-19.
Twitter COVID-19 Sentiment Analysis Members: Christopher Bach | Khalid Hamid Fallous | Jay Hirpara | Jing Tang | Graham Thomas | David Wetherhold Pro
Accelerating model creation and evaluation.
EmeraldML A machine learning library for streamlining the process of (1) cleaning and splitting data, (2) training, optimizing, and testing various mo
Codes for Causal Semantic Generative model (CSG), the model proposed in "Learning Causal Semantic Representation for Out-of-Distribution Prediction" (NeurIPS-21)
Learning Causal Semantic Representation for Out-of-Distribution Prediction This repository is the official implementation of "Learning Causal Semantic
IntraQ: Learning Synthetic Images with Intra-Class Heterogeneity for Zero-Shot Network Quantization
IntraQ: Learning Synthetic Images with Intra-Class Heterogeneity for Zero-Shot Network Quantization paper Requirements Python = 3.7.10 Pytorch == 1.7
New program to export a Blender model to the LBA2 model format.
LBA2 Blender to Model 2 This is a new program to export a Blender model to the LBA2 model format. This is also the first publicly released version of
[NeurIPS 2021 Spotlight] Code for Learning to Compose Visual Relations
Learning to Compose Visual Relations This is the pytorch codebase for the NeurIPS 2021 Spotlight paper Learning to Compose Visual Relations. Demo Imag
PyTorch implementation of Hierarchical Multi-label Text Classification: An Attention-based Recurrent Network
hierarchical-multi-label-text-classification-pytorch Hierarchical Multi-label Text Classification: An Attention-based Recurrent Network Approach This
This is a repository of our model for weakly-supervised video dense anticipation.
Introduction This is a repository of our model for weakly-supervised video dense anticipation. More results on GTEA, Epic-Kitchens etc. will come soon
Code and real data for the paper "Counterfactual Temporal Point Processes", available at arXiv.
counterfactual-tpp This is a repository containing code and real data for the paper Counterfactual Temporal Point Processes. Pre-requisites This code
Code for IntraQ, PyTorch implementation of our paper under review
IntraQ: Learning Synthetic Images with Intra-Class Heterogeneity for Zero-Shot Network Quantization paper Requirements Python = 3.7.10 Pytorch == 1.7
The implementation of DeBERTa
DeBERTa: Decoding-enhanced BERT with Disentangled Attention This repository is the official implementation of DeBERTa: Decoding-enhanced BERT with Dis
Simple image captioning model
CLIP prefix captioning. Inference Notebook: 🥳 New: 🥳 Our technical papar is finally out! Official implementation for the paper "ClipCap: CLIP Prefix
A pre-trained language model for social media text in Spanish
RoBERTuito A pre-trained language model for social media text in Spanish READ THE FULL PAPER Github Repository RoBERTuito is a pre-trained language mo
Flower classification model that classifies flowers in 10 classes made using transfer learning (~85% accuracy).
flower-classification-inceptionV3 Flower classification model that classifies flowers in 10 classes. Training and validation are done using a pre-anot
A multi-platform GUI for bit-based analysis, processing, and visualization
A multi-platform GUI for bit-based analysis, processing, and visualization
The code of NeurIPS 2021 paper "Scalable Rule-Based Representation Learning for Interpretable Classification".
Rule-based Representation Learner This is a PyTorch implementation of Rule-based Representation Learner (RRL) as described in NeurIPS 2021 paper: Scal
GemNet model in PyTorch, as proposed in "GemNet: Universal Directional Graph Neural Networks for Molecules" (NeurIPS 2021)
GemNet: Universal Directional Graph Neural Networks for Molecules Reference implementation in PyTorch of the geometric message passing neural network
Multi-modal Content Creation Model Training Infrastructure including the FACT model (AI Choreographer) implementation.
AI Choreographer: Music Conditioned 3D Dance Generation with AIST++ [ICCV-2021]. Overview This package contains the model implementation and training
Official source for spanish Language Models and resources made @ BSC-TEMU within the "Plan de las Tecnologías del Lenguaje" (Plan-TL).
Spanish Language Models 💃🏻 A repository part of the MarIA project. Corpora 📃 Corpora Number of documents Number of tokens Size (GB) BNE 201,080,084
Towards Calibrated Model for Long-Tailed Visual Recognition from Prior Perspective
Towards Calibrated Model for Long-Tailed Visual Recognition from Prior Perspective Zhengzhuo Xu, Zenghao Chai, Chun Yuan This is the PyTorch implement
This repo is about to create the Streamlit application for given ML model.
HR-Attritiion-using-Streamlit This repo is about to create the Streamlit application for given ML model. Problem Statement: Managing peoples at workpl
Stacked Generative Adversarial Networks
Stacked Generative Adversarial Networks This repository contains code for the paper "Stacked Generative Adversarial Networks", CVPR 2017. Part of the
Code for training and evaluation of the model from "Language Generation with Recurrent Generative Adversarial Networks without Pre-training"
Language Generation with Recurrent Generative Adversarial Networks without Pre-training Code for training and evaluation of the model from "Language G
Learning infinite-resolution image processing with GAN and RL from unpaired image datasets, using a differentiable photo editing model.
Exposure: A White-Box Photo Post-Processing Framework ACM Transactions on Graphics (presented at SIGGRAPH 2018) Yuanming Hu1,2, Hao He1,2, Chenxi Xu1,
A stable algorithm for GAN training
DRAGAN (Deep Regret Analytic Generative Adversarial Networks) Link to our paper - https://arxiv.org/abs/1705.07215 Pytorch implementation (thanks!) -
TensorFlow implementation of "Learning from Simulated and Unsupervised Images through Adversarial Training"
Simulated+Unsupervised (S+U) Learning in TensorFlow TensorFlow implementation of Learning from Simulated and Unsupervised Images through Adversarial T
Train CPPNs as a Generative Model, using Generative Adversarial Networks and Variational Autoencoder techniques to produce high resolution images.
cppn-gan-vae tensorflow Train Compositional Pattern Producing Network as a Generative Model, using Generative Adversarial Networks and Variational Aut
Tensorflow implementation of "BEGAN: Boundary Equilibrium Generative Adversarial Networks"
BEGAN in Tensorflow Tensorflow implementation of BEGAN: Boundary Equilibrium Generative Adversarial Networks. Requirements Python 2.7 or 3.x Pillow tq
The repository forked from NVlabs uses our data. (Differentiable rasterization applied to 3D model simplification tasks)
nvdiffmodeling [origin_code] Differentiable rasterization applied to 3D model simplification tasks, as described in the paper: Appearance-Driven Autom
Finding Label and Model Errors in Perception Data With Learned Observation Assertions
Finding Label and Model Errors in Perception Data With Learned Observation Assertions This is the project page for Finding Label and Model Errors in P
Powerful and efficient Computer Vision Annotation Tool (CVAT)
Computer Vision Annotation Tool (CVAT) CVAT is free, online, interactive video and image annotation tool for computer vision. It is being used by our
Collection of generative models in Tensorflow
tensorflow-generative-model-collections Tensorflow implementation of various GANs and VAEs. Related Repositories Pytorch version Pytorch version of th
Code of Classification Saliency-Based Rule for Visible and Infrared Image Fusion
CSF Code of Classification Saliency-Based Rule for Visible and Infrared Image Fusion Tips: For testing: CUDA_VISIBLE_DEVICES=0 python main.py For trai
Official implementation of the RAVE model: a Realtime Audio Variational autoEncoder
Official implementation of the RAVE model: a Realtime Audio Variational autoEncoder
A real-time approach for mapping all human pixels of 2D RGB images to a 3D surface-based model of the body
DensePose: Dense Human Pose Estimation In The Wild Rıza Alp Güler, Natalia Neverova, Iasonas Kokkinos [densepose.org] [arXiv] [BibTeX] Dense human pos
Semi-supervised Representation Learning for Remote Sensing Image Classification Based on Generative Adversarial Networks
SSRL-for-image-classification Semi-supervised Representation Learning for Remote Sensing Image Classification Based on Generative Adversarial Networks
Deploy pytorch classification model using Flask and Streamlit
Deploy pytorch classification model using Flask and Streamlit
Using graph_nets for pion classification and energy regression. Contributions from LLNL and LBNL
nbdev template Use this template to more easily create your nbdev project. If you are using an older version of this template, and want to upgrade to
CCQA A New Web-Scale Question Answering Dataset for Model Pre-Training
CCQA: A New Web-Scale Question Answering Dataset for Model Pre-Training This is the official repository for the code and models of the paper CCQA: A N
Simulation of early COVID-19 using SIR model and variants (SEIR ...).
COVID-19-simulation Simulation of early COVID-19 using SIR model and variants (SEIR ...). Made by the Laboratory of Sustainable Life Assessment (GYRO)
Implementation of the pix2pix model on satellite images
This repo shows how to implement and use the pix2pix GAN model for image to image translation. The model is demonstrated on satellite images, and the
Code for the TASLP paper "PSLA: Improving Audio Tagging With Pretraining, Sampling, Labeling, and Aggregation".
PSLA: Improving Audio Tagging with Pretraining, Sampling, Labeling, and Aggregation Introduction Getting Started FSD50K Recipe AudioSet Recipe Label E
[NeurIPS 2021] Deceive D: Adaptive Pseudo Augmentation for GAN Training with Limited Data
Deceive D: Adaptive Pseudo Augmentation for GAN Training with Limited Data (NeurIPS 2021) This repository will provide the official PyTorch implementa
RATE: Overcoming Noise and Sparsity of Textual Features in Real-Time Location Estimation (CIKM'17)
RATE: Overcoming Noise and Sparsity of Textual Features in Real-Time Location Estimation This is the implementation of RATE: Overcoming Noise and Spar
Code for DeepXML: A Deep Extreme Multi-Label Learning Framework Applied to Short Text Documents
DeepXML Code for DeepXML: A Deep Extreme Multi-Label Learning Framework Applied to Short Text Documents Architectures and algorithms DeepXML supports
Stochastic gradient descent with model building
Stochastic Model Building (SMB) This repository includes a new fast and robust stochastic optimization algorithm for training deep learning models. Th
Iterative Training: Finding Binary Weight Deep Neural Networks with Layer Binarization
Iterative Training: Finding Binary Weight Deep Neural Networks with Layer Binarization This repository contains the source code for the paper (link wi
⚖️🔁🔮🕵️♂️🦹🖼️ Code for *Measuring the Contribution of Multiple Model Representations in Detecting Adversarial Instances* paper.
Measuring the Contribution of Multiple Model Representations in Detecting Adversarial Instances This repository contains the code for Measuring the Co
Improving Compound Activity Classification via Deep Transfer and Representation Learning
Improving Compound Activity Classification via Deep Transfer and Representation Learning This repository is the official implementation of Improving C
Code and real data for the paper "Counterfactual Temporal Point Processes", available at arXiv.
counterfactual-tpp This is a repository containing code and real data for the paper Counterfactual Temporal Point Processes. Pre-requisites This code
Official code for: A Probabilistic Hard Attention Model For Sequentially Observed Scenes
"A Probabilistic Hard Attention Model For Sequentially Observed Scenes" Authors: Samrudhdhi Rangrej, James Clark Accepted to: BMVC'21 A recurrent atte
On Effective Scheduling of Model-based Reinforcement Learning
On Effective Scheduling of Model-based Reinforcement Learning Code to reproduce the experiments in On Effective Scheduling of Model-based Reinforcemen
KAPAO is an efficient multi-person human pose estimation model that detects keypoints and poses as objects and fuses the detections to predict human poses.
KAPAO (Keypoints and Poses as Objects) KAPAO is an efficient single-stage multi-person human pose estimation model that models keypoints and poses as
DataCLUE: 国内首个以数据为中心的AI测评(含模型分析报告)
DataCLUE: A Benchmark Suite for Data-centric NLP You can get the english version of README. 以数据为中心的AI测评(DataCLUE) 内容导引 章节 描述 简介 介绍以数据为中心的AI测评(DataCLUE
Extracting knowledge graphs from language models as a diagnostic benchmark of model performance.
Interpreting Language Models Through Knowledge Graph Extraction Idea: How do we interpret what a language model learns at various stages of training?
Source code for our EMNLP'21 paper 《Raise a Child in Large Language Model: Towards Effective and Generalizable Fine-tuning》
Child-Tuning Source code for EMNLP 2021 Long paper: Raise a Child in Large Language Model: Towards Effective and Generalizable Fine-tuning. 1. Environ
TaCL: Improving BERT Pre-training with Token-aware Contrastive Learning
TaCL: Improving BERT Pre-training with Token-aware Contrastive Learning Authors: Yixuan Su, Fangyu Liu, Zaiqiao Meng, Lei Shu, Ehsan Shareghi, and Nig
Interactive Web App with Streamlit and Scikit-learn that applies different Classification algorithms to popular datasets
Interactive Web App with Streamlit and Scikit-learn that applies different Classification algorithms to popular datasets Datasets Used: Iris dataset,
glTF to 3d Tiles Converter. Convert glTF model to Glb, b3dm or 3d tiles format.
gltf-to-3d-tiles glTF to 3d Tiles Converter. Convert glTF model to Glb, b3dm or 3d tiles format. Usage λ python main.py --help Usage: main.py [OPTION
Spectralformer: Rethinking hyperspectral image classification with transformers
The code in this toolbox implements the "Spectralformer: Rethinking hyperspectral image classification with transformers". More specifically, it is detailed as follow.
Short and long time series classification using convolutional neural networks
time-series-classification Short and long time series classification via convolutional neural networks In this project, we present a novel framework f
sktime companion package for deep learning based on TensorFlow
NOTE: sktime-dl is currently being updated to work correctly with sktime 0.6, and wwill be fully relaunched over the summer. The plan is Refactor and
ROCKET: Exceptionally fast and accurate time series classification using random convolutional kernels
ROCKET + MINIROCKET ROCKET: Exceptionally fast and accurate time series classification using random convolutional kernels. Data Mining and Knowledge D
Time Series Cross-Validation -- an extension for scikit-learn
TSCV: Time Series Cross-Validation This repository is a scikit-learn extension for time series cross-validation. It introduces gaps between the traini
Convoys is a simple library that fits a few statistical model useful for modeling time-lagged conversions.
Convoys is a simple library that fits a few statistical model useful for modeling time-lagged conversions. There is a lot more info if you head over to the documentation. You can also take a look at this blog post about Convoys.
A Python package for modular causal inference analysis and model evaluations
Causal Inference 360 A Python package for inferring causal effects from observational data. Description Causal inference analysis enables estimating t
moDel Agnostic Language for Exploration and eXplanation
moDel Agnostic Language for Exploration and eXplanation Overview Unverified black box model is the path to the failure. Opaqueness leads to distrust.
An open source AutoML toolkit for automate machine learning lifecycle, including feature engineering, neural architecture search, model compression and hyper-parameter tuning.
NNI Doc | 简体中文 NNI (Neural Network Intelligence) is a lightweight but powerful toolkit to help users automate Feature Engineering, Neural Architecture
Provide an input CSV and a target field to predict, generate a model + code to run it.
automl-gs Give an input CSV file and a target field you want to predict to automl-gs, and get a trained high-performing machine learning or deep learn
onelearn: Online learning in Python
onelearn: Online learning in Python Documentation | Reproduce experiments | onelearn stands for ONE-shot LEARNning. It is a small python package for o
Implementation of Uniformer, a simple attention and 3d convolutional net that achieved SOTA in a number of video classification tasks
Uniformer - Pytorch Implementation of Uniformer, a simple attention and 3d convolutional net that achieved SOTA in a number of video classification ta
ModelChimp is an experiment tracker for Deep Learning and Machine Learning experiments.
ModelChimp What is ModelChimp? ModelChimp is an experiment tracker for Deep Learning and Machine Learning experiments. ModelChimp provides the followi
BentoML is a flexible, high-performance framework for serving, managing, and deploying machine learning models.
Model Serving Made Easy BentoML is a flexible, high-performance framework for serving, managing, and deploying machine learning models. Supports multi
Metaflow is a human-friendly Python/R library that helps scientists and engineers build and manage real-life data science projects
Metaflow Metaflow is a human-friendly Python/R library that helps scientists and engineers build and manage real-life data science projects. Metaflow
YOLOX_AUDIO is an audio event detection model based on YOLOX
YOLOX_AUDIO is an audio event detection model based on YOLOX, an anchor-free version of YOLO. This repo is an implementated by PyTorch. Main goal of YOLOX_AUDIO is to detect and classify pre-defined audio events in multi-spectrogram domain using image object detection frameworks.
Use of Attention Gates in a Convolutional Neural Network / Medical Image Classification and Segmentation
Attention Gated Networks (Image Classification & Segmentation) Pytorch implementation of attention gates used in U-Net and VGG-16 models. The framewor
A Kitti Road Segmentation model implemented in tensorflow.
KittiSeg KittiSeg performs segmentation of roads by utilizing an FCN based model. The model achieved first place on the Kitti Road Detection Benchmark