2464 Repositories
Python Dust-model-dichotomous-performance-analysis Libraries
Exploratory data analysis
Exploratory data analysis An Exploratory data analysis APP TAPIWA CHAMBOKO 🚀 About Me I'm a full stack developer experienced in deploying artificial
Replication of Pix2Seq with Pretrained Model
Pretrained-Pix2Seq We provide the pre-trained model of Pix2Seq. This version contains new data augmentation. The model is trained for 300 epochs and c
Arch-Net: Model Distillation for Architecture Agnostic Model Deployment
Arch-Net: Model Distillation for Architecture Agnostic Model Deployment The official implementation of Arch-Net: Model Distillation for Architecture A
edaSQL is a library to link SQL to Exploratory Data Analysis and further more in the Data Engineering.
edaSQL is a python library to bridge the SQL with Exploratory Data Analysis where you can connect to the Database and insert the queries. The query results can be passed to the EDA tool which can give greater insights to the user.
Stock Analysis dashboard Using Streamlit and Python
StDashApp Stock Analysis Dashboard Using Streamlit and Python If you found the content useful and want to support my work, you can buy me a coffee! Th
Data-Driven Operational Space Control for Adaptive and Robust Robot Manipulation
OSCAR Project Page | Paper This repository contains the codebase used in OSCAR: Data-Driven Operational Space Control for Adaptive and Robust Robot Ma
[ICML'21] Estimate the accuracy of the classifier in various environments through self-supervision
What Does Rotation Prediction Tell Us about Classifier Accuracy under Varying Testing Environments? [Paper] [ICML'21 Project] PyTorch Implementation T
Perform sentiment analysis and keyword extraction on Craigslist listings
craiglist-helper synopsis Perform sentiment analysis and keyword extraction on Craigslist listings Background I love Craigslist. I've found most of my
Python-based tools for document analysis and OCR
ocropy OCRopus is a collection of document analysis programs, not a turn-key OCR system. In order to apply it to your documents, you may need to do so
This tool parses log data and allows to define analysis pipelines for anomaly detection.
logdata-anomaly-miner This tool parses log data and allows to define analysis pipelines for anomaly detection. It was designed to run the analysis wit
A collection of tools for biomedical research assay analysis in Python.
waltlabtools A collection of tools for biomedical research assay analysis in Python. Key Features Analysis for assays such as digital ELISA, including
Suite of tools for retrieving USGS NWIS observations and evaluating National Water Model (NWM) data.
Documentation OWPHydroTools GitHub pages documentation Motivation We developed OWPHydroTools with data scientists in mind. We attempted to ensure the
A Simple Framwork for CV Pre-training Model (SOCO, VirTex, BEiT)
A Simple Framwork for CV Pre-training Model (SOCO, VirTex, BEiT)
A pytorch-based real-time segmentation model for autonomous driving
CFPNet: Channel-Wise Feature Pyramid for Real-Time Semantic Segmentation This project contains the Pytorch implementation for the proposed CFPNet: pap
Code for EMNLP2021 paper "Allocating Large Vocabulary Capacity for Cross-lingual Language Model Pre-training"
VoCapXLM Code for EMNLP2021 paper Allocating Large Vocabulary Capacity for Cross-lingual Language Model Pre-training Environment DockerFile: dancingso
An Open-Source Toolkit for Prompt-Learning.
An Open-Source Framework for Prompt-learning. Overview • Installation • How To Use • Docs • Paper • Citation • What's New? Nov 2021: Now we have relea
For the paper entitled ''A Case Study and Qualitative Analysis of Simple Cross-Lingual Opinion Mining''
Summary This is the source code for the paper "A Case Study and Qualitative Analysis of Simple Cross-Lingual Opinion Mining", which was accepted as fu
Official implementation of "Multi-Glimpse Network: A Robust and Efficient Classification Architecture based on Recurrent Downsampled Attention" (BMVC 2021).
Multi-Glimpse Network Multi-Glimpse Network: A Robust and Efficient Classification Architecture based on Recurrent Downsampled Attention arXiv Require
Caboto, the Kubernetes semantic analysis tool
Caboto Caboto, the Kubernetes semantic analysis toolkit. It contains a lightweight Python library for semantic analysis of plain Kubernetes manifests
This project aims to be a handler for input creation and running of multiple RICEWQ simulations.
What is autoRICEWQ? This project aims to be a handler for input creation and running of multiple RICEWQ simulations. What is RICEWQ? From the descript
This repository has datasets containing information of Uber pickups in NYC from April 2014 to September 2014 and January to June 2015. data Analysis , virtualization and some insights are gathered here
uber-pickups-analysis Data Source: https://www.kaggle.com/fivethirtyeight/uber-pickups-in-new-york-city Information about data set The dataset contain
I created My own Virtual Artificial Intelligence named genesis, He can assist with my Tasks and also perform some analysis,,
Virtual-Artificial-Intelligence-genesis- I created My own Virtual Artificial Intelligence named genesis, He can assist with my Tasks and also perform
A python library for highly configurable transformers - easing model architecture search and experimentation.
A python library for highly configurable transformers - easing model architecture search and experimentation.
When in Doubt: Improving Classification Performance with Alternating Normalization
When in Doubt: Improving Classification Performance with Alternating Normalization Findings of EMNLP 2021 Menglin Jia, Austin Reiter, Ser-Nam Lim, Yoa
AutoTabular automates machine learning tasks enabling you to easily achieve strong predictive performance in your applications.
AutoTabular AutoTabular automates machine learning tasks enabling you to easily achieve strong predictive performance in your applications. With just
A python module for scientific analysis of 3D objects based on VTK and Numpy
A lightweight and powerful python module for scientific analysis and visualization of 3d objects.
A modular, research-friendly framework for high-performance and inference of sequence models at many scales
T5X T5X is a modular, composable, research-friendly framework for high-performance, configurable, self-service training, evaluation, and inference of
An efficient and easy-to-use deep learning model compression framework
TinyNeuralNetwork 简体中文 TinyNeuralNetwork is an efficient and easy-to-use deep learning model compression framework, which contains features like neura
CBMPy Metadraft: a flexible and extensible genome-scale model reconstruction tool
CBMPy Metadraft: a flexible and extensible, GUI-based genome-scale model reconstruction tool that supports multiple Systems Biology standards.
An atmospheric growth and evolution model based on the EVo degassing model and FastChem 2.0
EVolve Linking planetary mantles to atmospheric chemistry through volcanism using EVo and FastChem. Overview EVolve is a linked mantle degassing and a
FinEAS: Financial Embedding Analysis of Sentiment 📈
FinEAS: Financial Embedding Analysis of Sentiment 📈 (SentenceBERT for Financial News Sentiment Regression) This repository contains the code for gene
This repository contains the source code of an efficient 1D probabilistic model for music time analysis proposed in ICASSP2022 venue.
Jump Reward Inference for 1D Music Rhythmic State Spaces An implementation of the probablistic jump reward inference model for music rhythmic informat
RMNA: A Neighbor Aggregation-Based Knowledge Graph Representation Learning Model Using Rule Mining
RMNA: A Neighbor Aggregation-Based Knowledge Graph Representation Learning Model Using Rule Mining Our code is based on Learning Attention-based Embed
Implicit Model Specialization through DAG-based Decentralized Federated Learning
Federated Learning DAG Experiments This repository contains software artifacts to reproduce the experiments presented in the Middleware '21 paper "Imp
The code for the NeurIPS 2021 paper "A Unified View of cGANs with and without Classifiers".
Energy-based Conditional Generative Adversarial Network (ECGAN) This is the code for the NeurIPS 2021 paper "A Unified View of cGANs with and without
Analysis code and Latex source of the manuscript describing the conditional permutation test of confounding bias in predictive modelling.
Git repositoty of the manuscript entitled Statistical quantification of confounding bias in predictive modelling by Tamas Spisak The manuscript descri
Survival analysis (SA) is a well-known statistical technique for the study of temporal events.
DAGSurv Survival analysis (SA) is a well-known statistical technique for the study of temporal events. In SA, time-to-an-event data is modeled using a
K-FACE Analysis Project on Pytorch
Installation Setup with Conda # create a new environment conda create --name insightKface python=3.7 # or over conda activate insightKface #install t
Agent-based model simulator for air quality and pandemic risk assessment in architectural spaces
Agent-based model simulation for air quality and pandemic risk assessment in architectural spaces. User Guide archABM is a fast and open source agent-
A denoising diffusion probabilistic model synthesises galaxies that are qualitatively and physically indistinguishable from the real thing.
Realistic galaxy simulation via score-based generative models Official code for 'Realistic galaxy simulation via score-based generative models'. We us
Explore different way to mix speech model(wav2vec2, hubert) and nlp model(BART,T5,GPT) together
SpeechMix Explore different way to mix speech model(wav2vec2, hubert) and nlp model(BART,T5,GPT) together. Introduction For the same input: from datas
This is an auto-ML tool specialized in detecting of outliers
Auto-ML tool specialized in detecting of outliers Description This tool will allows you, with a Dash visualization, to compare 10 models of machine le
This is the official Pytorch implementation of the paper "Diverse Motion Stylization for Multiple Style Domains via Spatial-Temporal Graph-Based Generative Model"
Diverse Motion Stylization (Official) This is the official Pytorch implementation of this paper. Diverse Motion Stylization for Multiple Style Domains
Malware Analysis Neural Network project.
MalanaNeuralNetwork Description Malware Analysis Neural Network project. Table of Contents Getting Started Requirements Installation Clone Set-Up VENV
PyTorch implementation of a Real-ESRGAN model trained on custom dataset
Real-ESRGAN PyTorch implementation of a Real-ESRGAN model trained on custom dataset. This model shows better results on faces compared to the original
Developed an optimized algorithm which finds the most optimal path between 2 points in a 3D Maze using various AI search techniques like BFS, DFS, UCS, Greedy BFS and A*
Developed an optimized algorithm which finds the most optimal path between 2 points in a 3D Maze using various AI search techniques like BFS, DFS, UCS, Greedy BFS and A*. The algorithm was extremely optimal running in ~15s to ~30s for search spaces as big as 10000000 nodes where a set of 18 actions could be performed at each node in the 3D Maze.
this repository has datasets containing information of Uber pickups in NYC from April 2014 to September 2014 and January to June 2015. data Analysis , virtualization and some insights are gathered here
uber-pickups-analysis Data Source: https://www.kaggle.com/fivethirtyeight/uber-pickups-in-new-york-city Information about data set The dataset contain
An implementation on "Curved-Voxel Clustering for Accurate Segmentation of 3D LiDAR Point Clouds with Real-Time Performance"
Lidar-Segementation An implementation on "Curved-Voxel Clustering for Accurate Segmentation of 3D LiDAR Point Clouds with Real-Time Performance" from
A toolkit for geo ML data processing and model evaluation (fork of solaris)
An open source ML toolkit for overhead imagery. This is a beta version of lunular which may continue to develop. Please report any bugs through issues
Data cleaning tools for Business analysis
Datacleaning datacleaning tools for Business analysis This program is made for Vicky's work. You can use it, too. 数据清洗 该数据清洗工具是为了商业分析 这个程序是为了Vicky的工作而
Using Streamlit to host a multi-page tool with model specs and classification metrics, while also accepting user input values for prediction.
Predicitng_viability Using Streamlit to host a multi-page tool with model specs and classification metrics, while also accepting user input values for
Code for "Discovering Non-monotonic Autoregressive Orderings with Variational Inference" (paper and code updated from ICLR 2021)
Discovering Non-monotonic Autoregressive Orderings with Variational Inference Description This package contains the source code implementation of the
Python library for analysis of time series data including dimensionality reduction, clustering, and Markov model estimation
deeptime Releases: Installation via conda recommended. conda install -c conda-forge deeptime pip install deeptime Documentation: deeptime-ml.github.io
A Shading-Guided Generative Implicit Model for Shape-Accurate 3D-Aware Image Synthesis
A Shading-Guided Generative Implicit Model for Shape-Accurate 3D-Aware Image Synthesis Figure: Shape-Accurate 3D-Aware Image Synthesis. A Shading-Guid
A command line tool for visualizing CSV/spreadsheet-like data
PerfPlotter Read data from CSV files using pandas and generate interactive plots using bokeh, which can then be embedded into HTML pages and served by
A Factor Model for Persistence in Investment Manager Performance
Factor-Model-Manager-Performance A Factor Model for Persistence in Investment Manager Performance I apply methods and processes similar to those used
Simple GUI python app to show a stocks graph performance. Made with Matplotlib and Tiingo.
stock-graph-python Simple GUI python app to show a stocks graph performance. Made with Matplotlib and Tiingo. Tiingo API Key You will need to add your
ELFXtract is an automated analysis tool used for enumerating ELF binaries
ELFXtract ELFXtract is an automated analysis tool used for enumerating ELF binaries Powered by Radare2 and r2ghidra This is specially developed for PW
py-image-dedup is a tool to sort out or remove duplicates within a photo library
py-image-dedup is a tool to sort out or remove duplicates within a photo library. Unlike most other solutions, py-image-dedup intentionally uses an approximate image comparison to also detect duplicates of images that slightly differ in resolution, color or other minor details.
A complete end-to-end machine learning portal that covers processes starting from model training to the model predicting results using FastAPI.
Machine Learning Portal Goal Application Workflow Process Design Live Project Goal A complete end-to-end machine learning portal that covers processes
MsfMania is a command line tool developed in Python that is designed to bypass antivirus software on Windows and Linux/Mac in the future
MsfMania MsfMania is a command line tool developed in Python that is designed to bypass antivirus software on Windows and Linux/Mac in the future. Sum
A CLI Application to detect plagiarism in Source Code Files.
Plag Description A CLI Application to detect plagiarism in Source Code Files. Features Compare source code files for plagiarism. Extract code features
A simple tool to extract python code from a Jupyter notebook, and then run pylint on it for static analysis.
Jupyter Pylinter A simple tool to extract python code from a Jupyter notebook, and then run pylint on it for static analysis. If you find this tool us
[NeurIPS 2021] "Drawing Robust Scratch Tickets: Subnetworks with Inborn Robustness Are Found within Randomly Initialized Networks" by Yonggan Fu, Qixuan Yu, Yang Zhang, Shang Wu, Xu Ouyang, David Cox, Yingyan Lin
Drawing Robust Scratch Tickets: Subnetworks with Inborn Robustness Are Found within Randomly Initialized Networks Yonggan Fu, Qixuan Yu, Yang Zhang, S
A general, feasible, and extensible framework for classification tasks.
Pytorch Classification A general, feasible and extensible framework for 2D image classification. Features Easy to configure (model, hyperparameters) T
Open source single image super-resolution toolbox containing various functionality for training a diverse number of state-of-the-art super-resolution models. Also acts as the companion code for the IEEE signal processing letters paper titled 'Improving Super-Resolution Performance using Meta-Attention Layers’.
Deep-FIR Codebase - Super Resolution Meta Attention Networks About This repository contains the main coding framework accompanying our work on meta-at
A transformer model to predict pathogenic mutations
MutFormer MutFormer is an application of the BERT (Bidirectional Encoder Representations from Transformers) NLP (Natural Language Processing) model wi
State-of-the-art language models can match human performance on many tasks
Status: Archive (code is provided as-is, no updates expected) Grade School Math [Blog Post] [Paper] State-of-the-art language models can match human p
Easily Process a Batch of Cox Models
ezcox: Easily Process a Batch of Cox Models The goal of ezcox is to operate a batch of univariate or multivariate Cox models and return tidy result. ⏬
Official implementation of DreamerPro: Reconstruction-Free Model-Based Reinforcement Learning with Prototypical Representations in TensorFlow 2
DreamerPro Official implementation of DreamerPro: Reconstruction-Free Model-Based Reinforcement Learning with Prototypical Representations in TensorFl
[v1 (ISBI'21) + v2] MedMNIST: A Large-Scale Lightweight Benchmark for 2D and 3D Biomedical Image Classification
MedMNIST Project (Website) | Dataset (Zenodo) | Paper (arXiv) | MedMNIST v1 (ISBI'21) Jiancheng Yang, Rui Shi, Donglai Wei, Zequan Liu, Lin Zhao, Bili
OneFlow is a performance-centered and open-source deep learning framework.
OneFlow OneFlow is a performance-centered and open-source deep learning framework. Latest News Version 0.5.0 is out! First class support for eager exe
Colossal-AI: A Unified Deep Learning System for Large-Scale Parallel Training
ColossalAI An integrated large-scale model training system with efficient parallelization techniques. arXiv: Colossal-AI: A Unified Deep Learning Syst
UltraPose: Synthesizing Dense Pose with 1 Billion Points by Human-body Decoupling 3D Model
UltraPose: Synthesizing Dense Pose with 1 Billion Points by Human-body Decoupling 3D Model Official repository for the ICCV 2021 paper: UltraPose: Syn
This repository allows the user to automatically scale a 3D model/mesh/point cloud on Agisoft Metashape
Metashape-Utils This repository allows the user to automatically scale a 3D model/mesh/point cloud on Agisoft Metashape, given a set of 2D coordinates
A customized interface for single cell track visualisation based on pcnaDeep and napari.
pcnaDeep-napari A customized interface for single cell track visualisation based on pcnaDeep and napari. 👀 Under construction You can get test image
LightLog is an open source deep learning based lightweight log analysis tool for log anomaly detection.
LightLog Introduction LightLog is an open source deep learning based lightweight log analysis tool for log anomaly detection. Function description [BG
Identify and annotate mutations from genome editing assays.
CRISPR-detector Here we propose our CRISPR-detector to facilitate the CRISPR-edited amplicon and whole genome sequencing data analysis, with functions
A suite of benchmarks for CPU and GPU performance of the most popular high-performance libraries for Python :rocket:
A suite of benchmarks for CPU and GPU performance of the most popular high-performance libraries for Python :rocket:
A minimalist implementation of score-based diffusion model
sdeflow-light This is a minimalist codebase for training score-based diffusion models (supporting MNIST and CIFAR-10) used in the following paper "A V
A pre-trained model with multi-exit transformer architecture.
ElasticBERT This repository contains finetuning code and checkpoints for ElasticBERT. Towards Efficient NLP: A Standard Evaluation and A Strong Baseli
Data, model training, and evaluation code for "PubTables-1M: Towards a universal dataset and metrics for training and evaluating table extraction models".
PubTables-1M This repository contains training and evaluation code for the paper "PubTables-1M: Towards a universal dataset and metrics for training a
Implementation of Apriori Algorithm for Association Analysis
Implementation of Apriori Algorithm for Association Analysis
Spatial Interpolation Toolbox is a Python-based GUI that is able to interpolate spatial data in vector format.
Spatial Interpolation Toolbox This is the home to Spatial Interpolation Toolbox, a graphical user interface (GUI) for interpolating geographic vector
An interactive tool with which to explore the possible imaging performance of candidate ngEHT architectures.
ngEHTexplorer An interactive tool with which to explore the possible imaging performance of candidate ngEHT architectures. Welcome! ngEHTexplorer is a
Bendford analysis of Ethereum transaction
Bendford analysis of Ethereum transaction The python script script.py extract from already downloaded archive file the ethereum transaction. The value
Colossal-AI: A Unified Deep Learning System for Large-Scale Parallel Training
ColossalAI An integrated large-scale model training system with efficient parallelization techniques Installation PyPI pip install colossalai Install
AugMax: Adversarial Composition of Random Augmentations for Robust Training
[NeurIPS'21] "AugMax: Adversarial Composition of Random Augmentations for Robust Training" by Haotao Wang, Chaowei Xiao, Jean Kossaifi, Zhiding Yu, Animashree Anandkumar, and Zhangyang Wang.
A tensorflow model that predicts if the image is of a cat or of a dog.
Quick intro Hello and thank you for your interest in my project! This is the backend part of a two-repo application. The other part can be found here
K-means clustering is a method used for clustering analysis, especially in data mining and statistics.
K Means Algorithm What is K Means This algorithm is an iterative algorithm that partitions the dataset according to their features into K number of pr
Multiband spectro-radiometric satellite image analysis with K-means cluster algorithm
Multi-band Spectro Radiomertric Image Analysis with K-means Cluster Algorithm Overview Multi-band Spectro Radiomertric images are images comprising of
ElasticBERT: A pre-trained model with multi-exit transformer architecture.
This repository contains finetuning code and checkpoints for ElasticBERT. Towards Efficient NLP: A Standard Evaluation and A Strong Baseli
Anomaly Detection Based on Hierarchical Clustering of Mobile Robot Data
We proposed a new approach to detect anomalies of mobile robot data. We investigate each data seperately with two clustering method hierarchical and k-means. There are two sub-method that we used for produce an anomaly score. Then, we merge these two score and produce merged anomaly score as a result.
Implementation of PersonaGPT Dialog Model
PersonaGPT An open-domain conversational agent with many personalities PersonaGPT is an open-domain conversational agent cpable of decoding personaliz
This is a five-step framework for the development of intrusion detection systems (IDS) using machine learning (ML) considering model realization, and performance evaluation.
AB-TRAP: building invisibility shields to protect network devices The AB-TRAP framework is applicable to the development of Network Intrusion Detectio
Can we visualize a large scientific data set with a surrogate model? We're building a GAN for the Earth's Mantle Convection data set to see if we can!
EarthGAN - Earth Mantle Surrogate Modeling Can a surrogate model of the Earth’s Mantle Convection data set be built such that it can be readily run in
Nested Graph Neural Network (NGNN) is a general framework to improve a base GNN's expressive power and performance
Nested Graph Neural Networks About Nested Graph Neural Network (NGNN) is a general framework to improve a base GNN's expressive power and performance.
Implementation of several Bayesian multi-target tracking algorithms, including Poisson multi-Bernoulli mixture filters for sets of targets and sets of trajectories. The repository also includes the GOSPA metric and a metric for sets of trajectories to evaluate performance.
This repository contains the Matlab implementations for the following multi-target filtering/tracking algorithms: - Folder PMBM contains the implemen
[NeurIPS'21] "AugMax: Adversarial Composition of Random Augmentations for Robust Training" by Haotao Wang, Chaowei Xiao, Jean Kossaifi, Zhiding Yu, Animashree Anandkumar, and Zhangyang Wang.
AugMax: Adversarial Composition of Random Augmentations for Robust Training Haotao Wang, Chaowei Xiao, Jean Kossaifi, Zhiding Yu, Anima Anandkumar, an
Probabilistic Entity Representation Model for Reasoning over Knowledge Graphs
Implementation for the paper: Probabilistic Entity Representation Model for Reasoning over Knowledge Graphs, Nurendra Choudhary, Nikhil Rao, Sumeet Ka