2325 Repositories
Python graph-attention-model Libraries
The Instructed Glacier Model (IGM)
The Instructed Glacier Model (IGM) Overview The Instructed Glacier Model (IGM) simulates the ice dynamics, surface mass balance, and its coupling thro
A small collection of tools made by me, that you can use to visualize atomic orbitals in both 2D and 3D in different aspects.
Orbitals in Python A small collection of tools made by me, that you can use to visualize atomic orbitals in both 2D and 3D in different aspects, and o
Official implementation of SIGIR'2021 paper: "Sequential Recommendation with Graph Neural Networks".
SURGE: Sequential Recommendation with Graph Neural Networks This is our TensorFlow implementation for the paper: Sequential Recommendation with Graph
Tandem Mass Spectrum Prediction with Graph Transformers
MassFormer This is the original implementation of MassFormer, a graph transformer for small molecule MS/MS prediction. Check out the preprint on arxiv
ChebLieNet, a spectral graph neural network turned equivariant by Riemannian geometry on Lie groups.
ChebLieNet: Invariant spectral graph NNs turned equivariant by Riemannian geometry on Lie groups Hugo Aguettaz, Erik J. Bekkers, Michaël Defferrard We
Using Language Model to Bootstrap Human Activity Recognition Ambient Sensors Based in Smart Homes
Using Language Model to Bootstrap Human Activity Recognition Ambient Sensors Based in Smart Homes This repository is the official implementation of Us
Official Codes for Graph Modularity:Towards Understanding the Cross-Layer Transition of Feature Representations in Deep Neural Networks.
Dynamic-Graphs-Construction Official Codes for Graph Modularity:Towards Understanding the Cross-Layer Transition of Feature Representations in Deep Ne
CLIPImageClassifier wraps clip image model from transformers
CLIPImageClassifier CLIPImageClassifier wraps clip image model from transformers. CLIPImageClassifier is initialized with the argument classes, these
Portfolio Optimization and Quantitative Strategic Asset Allocation in Python
Riskfolio-Lib Quantitative Strategic Asset Allocation, Easy for Everyone. Description Riskfolio-Lib is a library for making quantitative strategic ass
Two-Stream Adaptive Graph Convolutional Networks for Skeleton-Based Action Recognition in CVPR19
2s-AGCN Two-Stream Adaptive Graph Convolutional Networks for Skeleton-Based Action Recognition in CVPR19 Note PyTorch version should be 0.3! For PyTor
A naive Bayes model for cancer classification using a set of documents
Naivebayes text classifcation model for cancer and noncancer documents Author: Alex King Purpose Requirements/files included How to use 1. Purpose The
Graph parsing approach to structured sentiment analysis.
Fine-grained Sentiment Analysis as Dependency Graph Parsing This repository contains the code and datasets described in following paper: Fine-grained
Switch spaces for knowledge graph embeddings
SwisE Switch spaces for knowledge graph embeddings. Requirements: python3 pytorch numpy tqdm Reproduce the results To reproduce the reported results,
Delve is a Python package for analyzing the inference dynamics of your PyTorch model.
Delve is a Python package for analyzing the inference dynamics of your PyTorch model.
fastai ulmfit - Pretraining the Language Model, Fine-Tuning and training a Classifier
fast.ai ULMFiT with SentencePiece from pretraining to deployment Motivation: Why even bother with a non-BERT / Transformer language model? Short answe
Deep Reinforced Attention Regression for Partial Sketch Based Image Retrieval.
DARP-SBIR Intro This repository contains the source code implementation for ICDM submission paper Deep Reinforced Attention Regression for Partial Ske
A framework for annotating 3D meshes using the predictions of a 2D semantic segmentation model.
Semantic Meshes A framework for annotating 3D meshes using the predictions of a 2D semantic segmentation model. Paper If you find this framework usefu
Graph Convolutional Neural Networks with Data-driven Graph Filter (GCNN-DDGF)
Graph Convolutional Gated Recurrent Neural Network (GCGRNN) Improved from Graph Convolutional Neural Networks with Data-driven Graph Filter (GCNN-DDGF
DivNoising is an unsupervised denoising method to generate diverse denoised samples for any noisy input image. This repository contains the code to reproduce the results reported in the paper https://openreview.net/pdf?id=agHLCOBM5jP
DivNoising: Diversity Denoising with Fully Convolutional Variational Autoencoders Mangal Prakash1, Alexander Krull1,2, Florian Jug2 1Authors contribut
An example project using OpenPrompt under pytorch-lightning for prompt-based SST2 sentiment analysis model
pl_prompt_sst An example project using OpenPrompt under the framework of pytorch-lightning for a training prompt-based text classification model on SS
Unofficial keras(tensorflow) implementation of MAE model from Masked Autoencoders Are Scalable Vision Learners
MAE-keras Unofficial keras(tensorflow) implementation of MAE model described in 'Masked Autoencoders Are Scalable Vision Learners'. This work has been
Tensorflow 2.x implementation of Vision-Transformer model
Vision Transformer Unofficial Tensorflow 2.x implementation of the Transformer based Image Classification model proposed by the paper AN IMAGE IS WORT
State of the art faster Natural Language Processing in Tensorflow 2.0 .
tf-transformers: faster and easier state-of-the-art NLP in TensorFlow 2.0 ****************************************************************************
A python library for decision tree visualization and model interpretation.
dtreeviz : Decision Tree Visualization Description A python library for decision tree visualization and model interpretation. Currently supports sciki
Python library for interactive topic model visualization. Port of the R LDAvis package.
pyLDAvis Python library for interactive topic model visualization. This is a port of the fabulous R package by Carson Sievert and Kenny Shirley. pyLDA
Option Pricing Calculator using the Binomial Pricing Method (No Libraries Required)
Binomial Option Pricing Calculator Option Pricing Calculator using the Binomial Pricing Method (No Libraries Required) Background A derivative is a fi
Backprop makes it simple to use, finetune, and deploy state-of-the-art ML models.
Backprop makes it simple to use, finetune, and deploy state-of-the-art ML models. Solve a variety of tasks with pre-trained models or finetune them in
Ultra-lightweight human body posture key point CNN model. ModelSize:2.3MB HUAWEI P40 NCNN benchmark: 6ms/img,
Ultralight-SimplePose Support NCNN mobile terminal deployment Based on MXNET(=1.5.1) GLUON(=0.7.0) framework Top-down strategy: The input image is t
Quantization library for PyTorch. Support low-precision and mixed-precision quantization, with hardware implementation through TVM.
HAWQ: Hessian AWare Quantization HAWQ is an advanced quantization library written for PyTorch. HAWQ enables low-precision and mixed-precision uniform
An Active Automata Learning Library Written in Python
AALpy An Active Automata Learning Library AALpy is a light-weight active automata learning library written in pure Python. You can start learning auto
Code accompanying the paper "ProxyFL: Decentralized Federated Learning through Proxy Model Sharing"
ProxyFL Code accompanying the paper "ProxyFL: Decentralized Federated Learning through Proxy Model Sharing" Authors: Shivam Kalra*, Junfeng Wen*, Jess
Multiple types of NN model optimization environments. It is possible to directly access the host PC GUI and the camera to verify the operation. Intel iHD GPU (iGPU) support. NVIDIA GPU (dGPU) support.
mtomo Multiple types of NN model optimization environments. It is possible to directly access the host PC GUI and the camera to verify the operation.
A tutorial on training a DarkNet YOLOv4 model for the CrowdHuman dataset
YOLOv4 CrowdHuman Tutorial This is a tutorial demonstrating how to train a YOLOv4 people detector using Darknet and the CrowdHuman dataset. Table of c
A Python package for performing pore network modeling of porous media
Overview of OpenPNM OpenPNM is a comprehensive framework for performing pore network simulations of porous materials. More Information For more detail
DA2Lite is an automated model compression toolkit for PyTorch.
DA2Lite (Deep Architecture to Lite) is a toolkit to compress and accelerate deep network models. ⭐ Star us on GitHub — it helps!! Frameworks & Librari
A keras-based real-time model for medical image segmentation (CFPNet-M)
CFPNet-M: A Light-Weight Encoder-Decoder Based Network for Multimodal Biomedical Image Real-Time Segmentation This repository contains the implementat
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
Codebase for "ProtoAttend: Attention-Based Prototypical Learning."
Codebase for "ProtoAttend: Attention-Based Prototypical Learning." Authors: Sercan O. Arik and Tomas Pfister Paper: Sercan O. Arik and Tomas Pfister,
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.
Optimal skincare partition finder using graph theory
Pigment The problem of partitioning up a skincare regime into parts such that each part does not interfere with itself is equivalent to the minimal cl
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
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.
You Only Look At CoefficienTs ██╗ ██╗ ██████╗ ██╗ █████╗ ██████╗████████╗ ╚██╗ ██╔╝██╔═══██╗██║ ██╔══██╗██╔════╝╚══██╔══╝ ╚██
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
A denoising autoencoder + adversarial losses and attention mechanisms for face swapping.
faceswap-GAN Adding Adversarial loss and perceptual loss (VGGface) to deepfakes'(reddit user) auto-encoder architecture. Updates Date Update 2018-08-2
NLP and Text Generation Experiments in TensorFlow 2.x / 1.x
Code has been run on Google Colab, thanks Google for providing computational resources Contents Natural Language Processing(自然语言处理) Text Classificati
nlp-tutorial is a tutorial for who is studying NLP(Natural Language Processing) using Pytorch
nlp-tutorial is a tutorial for who is studying NLP(Natural Language Processing) using Pytorch. Most of the models in NLP were implemented with less than 100 lines of code.(except comments or blank lines)
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
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
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
It's an application to calculate I from v and r. It can also plot a graph between V vs I.
Ohm-s-Law-Visualizer It's an application to calculate I from v and r using Ohm's Law. It can also plot a graph between V vs I. Story I'm doing my Unde
Implementing Graph Convolutional Networks and Information Retrieval Mechanisms using pure Python and NumPy
Implementing Graph Convolutional Networks and Information Retrieval Mechanisms using pure Python and NumPy
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
Official repository for the paper "GN-Transformer: Fusing AST and Source Code information in Graph Networks".
GN-Transformer AST This is the official repository for the paper "GN-Transformer: Fusing AST and Source Code information in Graph Networks". Data Prep
You Only Sample (Almost) Once: Linear Cost Self-Attention Via Bernoulli Sampling
You Only Sample (Almost) Once: Linear Cost Self-Attention Via Bernoulli Sampling Transformer-based models are widely used in natural language processi
Bio-Computing Platform Featuring Large-Scale Representation Learning and Multi-Task Deep Learning “螺旋桨”生物计算工具集
English | 简体中文 Latest News 2021.10.25 Paper "Docking-based Virtual Screening with Multi-Task Learning" is accepted by BIBM 2021. 2021.07.29 PaddleHeli
RAANet: Range-Aware Attention Network for LiDAR-based 3D Object Detection with Auxiliary Density Level Estimation
RAANet: Range-Aware Attention Network for LiDAR-based 3D Object Detection with Auxiliary Density Level Estimation Anonymous submission Abstract 3D obj
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
Self-attentive task GAN for space domain awareness data augmentation.
SATGAN TODO: update the article URL once published. Article about this implemention The self-attentive task generative adversarial network (SATGAN) le
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
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
A PyTorch implementation of "CoAtNet: Marrying Convolution and Attention for All Data Sizes".
CoAtNet Overview This is a PyTorch implementation of CoAtNet specified in "CoAtNet: Marrying Convolution and Attention for All Data Sizes", arXiv 2021
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
TensorFlow GNN is a library to build Graph Neural Networks on the TensorFlow platform.
TensorFlow GNN This is an early (alpha) release to get community feedback. It's under active development and we may break API compatibility in the fut
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
Some tentative models that incorporate label propagation to graph neural networks for graph representation learning in nodes, links or graphs.
Some tentative models that incorporate label propagation to graph neural networks for graph representation learning in nodes, links or graphs.
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
Extract rooms type, door, neibour rooms, rooms corners nad bounding boxes, and generate graph from rplan dataset
Housegan-data-reader House-GAN++ (data-reader) Code and instructions for converting rplan dataset (raster images) to housegan++ data format. House-GAN
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
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
Build Graph Nets in Tensorflow
Graph Nets library Graph Nets is DeepMind's library for building graph networks in Tensorflow and Sonnet. Contact [email protected] for comments a
Sky attention heatmap of submissions to astrometry.net
astroheat Installation Requires Python 3.6+, Tested with Python 3.9.5 Install library dependencies pip install -r requirements.txt The program require
This is the repository for the AAAI 21 paper [Contrastive and Generative Graph Convolutional Networks for Graph-based Semi-Supervised Learning].
CG3 This is the repository for the AAAI 21 paper [Contrastive and Generative Graph Convolutional Networks for Graph-based Semi-Supervised Learning]. R