181 Repositories
Python resting-state Libraries
Easy-to-use library to boost AI inference leveraging state-of-the-art optimization techniques.
NEW RELEASE How Nebullvm Works • Tutorials • Benchmarks • Installation • Get Started • Optimization Examples Discord | Website | LinkedIn | Twitter Ne
HugsVision is a easy to use huggingface wrapper for state-of-the-art computer vision
HugsVision is an open-source and easy to use all-in-one huggingface wrapper for computer vision. The goal is to create a fast, flexible and user-frien
Use the state-of-the-art m2m100 to translate large data on CPU/GPU/TPU. Super Easy!
Easy-Translate is a script for translating large text files in your machine using the M2M100 models from Facebook/Meta AI. We also privide a script fo
Implementation of ETSformer, state of the art time-series Transformer, in Pytorch
ETSformer - Pytorch Implementation of ETSformer, state of the art time-series Transformer, in Pytorch Install $ pip install etsformer-pytorch Usage im
A Decentralized Omnidirectional Visual-Inertial-UWB State Estimation System for Aerial Swar.
Omni-swarm A Decentralized Omnidirectional Visual-Inertial-UWB State Estimation System for Aerial Swarm Introduction Omni-swarm is a decentralized omn
Package towards building Explainable Forecasting and Nowcasting Models with State-of-the-art Deep Neural Networks and Dynamic Factor Model on Time Series data sets with single line of code. Also, provides utilify facility for time-series signal similarities matching, and removing noise from timeseries signals.
DeepXF: Explainable Forecasting and Nowcasting with State-of-the-art Deep Neural Networks and Dynamic Factor Model Also, verify TS signal similarities
🚀 RocketQA, dense retrieval for information retrieval and question answering, including both Chinese and English state-of-the-art models.
In recent years, the dense retrievers based on pre-trained language models have achieved remarkable progress. To facilitate more developers using cutt
TorchMultimodal is a PyTorch library for training state-of-the-art multimodal multi-task models at scale.
TorchMultimodal (Alpha Release) Introduction TorchMultimodal is a PyTorch library for training state-of-the-art multimodal multi-task models at scale.
Implementation of 🦩 Flamingo, state-of-the-art few-shot visual question answering attention net out of Deepmind, in Pytorch
🦩 Flamingo - Pytorch Implementation of Flamingo, state-of-the-art few-shot visual question answering attention net, in Pytorch. It will include the p
Implementation of the state-of-the-art vision transformers with tensorflow
ViT Tensorflow This repository contains the tensorflow implementation of the state-of-the-art vision transformers (a category of computer vision model
KalmanFilterExercise - A Kalman Filter is a algorithmic filter that is used to estimate the state of an unknown variable
Kalman Filter Exercise What are Kalman Filters? A Kalman Filter is a algorithmic
TorchMD-Net provides state-of-the-art graph neural networks and equivariant transformer neural networks potentials for learning molecular potentials
TorchMD-net TorchMD-Net provides state-of-the-art graph neural networks and equivariant transformer neural networks potentials for learning molecular
PyTorch implementation of SMODICE: Versatile Offline Imitation Learning via State Occupancy Matching
SMODICE: Versatile Offline Imitation Learning via State Occupancy Matching This is the official PyTorch implementation of SMODICE: Versatile Offline I
Natural language processing summarizer using 3 state of the art Transformer models: BERT, GPT2, and T5
NLP-Summarizer Natural language processing summarizer using 3 state of the art Transformer models: BERT, GPT2, and T5 This project aimed to provide in
A performant state estimator for power system
A state estimator for power system. Turbocharged with sparse matrix support, JIT, SIMD and improved ordering.
This tool converts a Nondeterministic Finite Automata (NFA) into a Deterministic Finite Automata (DFA)
This tool converts a Nondeterministic Finite Automata (NFA) into a Deterministic Finite Automata (DFA)
AttractionFinder - 2022 State Qualified FBLA Attraction Finder Application
Attraction Finder Developers: Riyon Praveen, Aaron Bijoy, & Yash Vora How It Wor
A tool for study using pomodoro methodology, while study mode spotify or any other .exe app is opened and while resting is closed.
Pomodoro-Timer-With-Spotify-Connection A tool for study using pomodoro methodology, while study mode spotify or any other .exe app is opened and while
In this workshop we will be exploring NLP state of the art transformers, with SOTA models like T5 and BERT, then build a model using HugginFace transformers framework.
Transformers are all you need In this workshop we will be exploring NLP state of the art transformers, with SOTA models like T5 and BERT, then build a
Downloads state flags from wikipedia for states/regions from all countries
world-state-flags Downloads state flags from wikipedia for states/regions from all countries This data is NOT curated Uses https://github.com/dr5hn/co
EASY - Ensemble Augmented-Shot Y-shaped Learning: State-Of-The-Art Few-Shot Classification with Simple Ingredients.
EASY - Ensemble Augmented-Shot Y-shaped Learning: State-Of-The-Art Few-Shot Classification with Simple Ingredients. This repository is the official im
An experiment on the performance of homemade Q-learning AIs in Agar.io depending on their state representation and available actions
Agar.io_Q-Learning_AI An experiment on the performance of homemade Q-learning AIs in Agar.io depending on their state representation and available act
This is a classifier which basically predicts whether there is a gun law in a state or not, depending on various things like murder rates etc.
Gun-Laws-Classifier This is a classifier which basically predicts whether there is a gun law in a state or not, depending on various things like murde
A complete, self-contained example for training ImageNet at state-of-the-art speed with FFCV
ffcv ImageNet Training A minimal, single-file PyTorch ImageNet training script designed for hackability. Run train_imagenet.py to get... ...high accur
Few-Shot-Intent-Detection includes popular challenging intent detection datasets with/without OOS queries and state-of-the-art baselines and results.
Few-Shot-Intent-Detection Few-Shot-Intent-Detection is a repository designed for few-shot intent detection with/without Out-of-Scope (OOS) intents. It
Just a simple python script to generate graphs of salt state requisites.
saltstatevis Just a simple python script to generate graphs of salt state requisites. Installation Requirements You will need to install graphviz to r
Linear Variational State Space Filters
Linear Variational State Space Filters To set up the environment, use the provided scripts in the docker/ folder to build and run the codebase inside
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
Semantic similarity computation with different state-of-the-art metrics
Semantic similarity computation with different state-of-the-art metrics Description • Installation • Usage • License Description TaxoSS is a semantic
Fully Convlutional Neural Networks for state-of-the-art time series classification
Deep Learning for Time Series Classification As the simplest type of time series data, univariate time series provides a reasonably good starting poin
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
A curated list of the top 10 computer vision papers in 2021 with video demos, articles, code and paper reference.
The Top 10 Computer Vision Papers of 2021 The top 10 computer vision papers in 2021 with video demos, articles, code, and paper reference. While the w
State-Relabeling Adversarial Active Learning
State-Relabeling Adversarial Active Learning Code for SRAAL [2020 CVPR Oral] Requirements torch = 1.6.0 numpy = 1.19.1 tqdm = 4.31.1 AL Results The
AAAI-22 paper: SimSR: Simple Distance-based State Representationfor Deep Reinforcement Learning
SimSR Code and dataset for the paper SimSR: Simple Distance-based State Representationfor Deep Reinforcement Learning (AAAI-22). Requirements We assum
Imports VZD (Latvian State Land Service) open data into postgis enabled database
Python script main.py downloads and imports Latvian addresses into PostgreSQL database. Data contains parishes, counties, cities, towns, and streets.
Saliency - Framework-agnostic implementation for state-of-the-art saliency methods (XRAI, BlurIG, SmoothGrad, and more).
Saliency Methods 🔴 Now framework-agnostic! (Example core notebook) 🔴 🔗 For further explanation of the methods and more examples of the resulting ma
A state-of-the-art semi-supervised method for image recognition
Mean teachers are better role models Paper ---- NIPS 2017 poster ---- NIPS 2017 spotlight slides ---- Blog post By Antti Tarvainen, Harri Valpola (The
Datasets for new state-of-the-art challenge in disentanglement learning
High resolution disentanglement datasets This repository contains the Falcor3D and Isaac3D datasets, which present a state-of-the-art challenge for co
LAVT: Language-Aware Vision Transformer for Referring Image Segmentation
LAVT: Language-Aware Vision Transformer for Referring Image Segmentation Where we are ? 12.27 目前和原论文仍有1%左右得差距,但已经力压很多SOTA了 ckpt__448_epoch_25.pth mIoU
Terraform wrapper to manage state across multiple cloud providers(AWS, GCP, and Azure)
Terraform Remote State Manager(tfremote) tf is a python package for managing terraform remote state for: Google(Gcloud), AWS, and Azure. It sets a def
Code for "Unsupervised State Representation Learning in Atari"
Unsupervised State Representation Learning in Atari Ankesh Anand*, Evan Racah*, Sherjil Ozair*, Yoshua Bengio, Marc-Alexandre Côté, R Devon Hjelm This
A curated list of the latest breakthroughs in AI (in 2021) by release date with a clear video explanation, link to a more in-depth article, and code.
2021: A Year Full of Amazing AI papers- A Review 📌 A curated list of the latest breakthroughs in AI by release date with a clear video explanation, l
Open-source library for analyzing the results produced by ABINIT
Package Continuous Integration Documentation About AbiPy is a python library to analyze the results produced by Abinit, an open-source program for the
Official code for article "Expression is enough: Improving traffic signal control with advanced traffic state representation"
1 Introduction Official code for article "Expression is enough: Improving traffic signal control with advanced traffic state representation". The code s
Machine learning algorithms for many-body quantum systems
NetKet NetKet is an open-source project delivering cutting-edge methods for the study of many-body quantum systems with artificial neural networks and
Tools for the Cleveland State Human Motion and Control Lab
Introduction This is a collection of tools that are helpful for gait analysis. Some are specific to the needs of the Human Motion and Control Lab at C
Almost State-of-the-art Text Generation library
Ps: we are adding transformer model soon Text Gen 🐐 Almost State-of-the-art Text Generation library Text gen is a python library that allow you build
🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.
English | 简体中文 | 繁體中文 | 한국어 State-of-the-art Machine Learning for JAX, PyTorch and TensorFlow 🤗 Transformers provides thousands of pretrained models
A high-performance distributed deep learning system targeting large-scale and automated distributed training.
HETU Documentation | Examples Hetu is a high-performance distributed deep learning system targeting trillions of parameters DL model training, develop
Oregon State University grade distributions from Fall 2018 through Summer 2021
Oregon State University Grades Oregon State University grade distributions from Fall 2018 through Summer 2021 obtained through a Freedom Of Informatio
Periodically check the manuscript state in the scholar one system and send email when finding a new state.
ScholarOne-manuscript-checker Periodically check the manuscript state in the scholar one system and send email when finding a new state. Parameters ne
State-of-the-art NLP through transformer models in a modular design and consistent APIs.
Trapper (Transformers wRAPPER) Trapper is an NLP library that aims to make it easier to train transformer based models on downstream tasks. It wraps h
A python script to poll RPi GPIO pins and subscribe and publish their state via MQTT
MQTT-GPIO A python script to poll RPi GPIO pins and subscribe and publish their state via MQTT using TLS. This script is short and meant to be edited
Implementation of NÜWA, state of the art attention network for text to video synthesis, in Pytorch
NÜWA - Pytorch (wip) Implementation of NÜWA, state of the art attention network for text to video synthesis, in Pytorch. This repository will be popul
Motion planning algorithms commonly used on autonomous vehicles. (path planning + path tracking)
Overview This repository implemented some common motion planners used on autonomous vehicles, including Hybrid A* Planner Frenet Optimal Trajectory Hi
A simple python script using Numpy and Matplotlib library to plot a Mohr's Circle when given a two-dimensional state of stress.
Mohr's Circle Calculator This is a really small personal project done for Department of Civil Engineering, Delhi Technological University (formerly, D
AAAI 2022: Stationary diffusion state neural estimation
Stationary Diffusion State Neural Estimation Although many graph-based clustering methods attempt to model the stationary diffusion state in their obj
CoRe: Contrastive Recurrent State-Space Models
CoRe: Contrastive Recurrent State-Space Models This code implements the CoRe model and reproduces experimental results found in Robust Robotic Control
A Python library for simulating finite automata, pushdown automata, and Turing machines
Automata Copyright 2016-2021 Caleb Evans Released under the MIT license Automata is a Python 3 library which implements the structures and algorithms
NALSM: Neuron-Astrocyte Liquid State Machine
NALSM: Neuron-Astrocyte Liquid State Machine This package is a Tensorflow implementation of the Neuron-Astrocyte Liquid State Machine (NALSM) that int
Code for models used in Bashiri et al., "A Flow-based latent state generative model of neural population responses to natural images".
A Flow-based latent state generative model of neural population responses to natural images Code for "A Flow-based latent state generative model of ne
PySlowFast: video understanding codebase from FAIR for reproducing state-of-the-art video models.
PySlowFast PySlowFast is an open source video understanding codebase from FAIR that provides state-of-the-art video classification models with efficie
A Flask wrapper of Starknet state. Similar in purpose to Ganache.
Introduction A Flask wrapper of Starknet state. Similar in purpose to Ganache. Aims to mimic Starknet's Alpha testnet, but with simplified functionali
This repository provides an unified frameworks to train and test the state-of-the-art few-shot font generation (FFG) models.
FFG-benchmarks This repository provides an unified frameworks to train and test the state-of-the-art few-shot font generation (FFG) models. What is Fe
Implementation of the MDMC method to search for magnetic ground state using VASP
Implementation of MDMC method ( by Olga Vekilova ) to search for magnetic ground state using VASP
Text Extraction Formulation + Feedback Loop for state-of-the-art WSD (EMNLP 2021)
ConSeC is a novel approach to Word Sense Disambiguation (WSD), accepted at EMNLP 2021. It frames WSD as a text extraction task and features a feedback loop strategy that allows the disambiguation of a target word to be conditioned not only on its context but also on the explicit senses assigned to nearby words.
This thesis is mainly concerned with state-space methods for a class of deep Gaussian process (DGP) regression problems
Doctoral dissertation of Zheng Zhao This thesis is mainly concerned with state-space methods for a class of deep Gaussian process (DGP) regression pro
An easy to use Natural Language Processing library and framework for predicting, training, fine-tuning, and serving up state-of-the-art NLP models.
Welcome to AdaptNLP A high level framework and library for running, training, and deploying state-of-the-art Natural Language Processing (NLP) models
Current state of supervised and unsupervised depth completion methods
Awesome Depth Completion Table of Contents About Sparse-to-Dense Depth Completion Current State of Depth Completion Unsupervised VOID Benchmark Superv
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 3 package for state-of-the-art statistical dimension reduction methods
direpack: a Python 3 library for state-of-the-art statistical dimension reduction techniques This package delivers a scikit-learn compatible Python 3
This script scrapes and stores the availability of timeslots for Car Driving Test at all RTA Serivce NSW centres in the state.
This script scrapes and stores the availability of timeslots for Car Driving Test at all RTA Serivce NSW centres in the state. Dependencies Account wi
Kubediff: a tool for Kubernetes to show differences between running state and version controlled configuration.
Kubediff: a tool for Kubernetes to show differences between running state and version controlled configuration.
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
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
The Fundamental Clustering Problems Suite (FCPS) summaries 54 state-of-the-art clustering algorithms, common cluster challenges and estimations of the number of clusters as well as the testing for cluster tendency.
FCPS Fundamental Clustering Problems Suite The package provides over sixty state-of-the-art clustering algorithms for unsupervised machine learning pu
RRxIO - Robust Radar Visual/Thermal Inertial Odometry: Robust and accurate state estimation even in challenging visual conditions.
RRxIO - Robust Radar Visual/Thermal Inertial Odometry RRxIO offers robust and accurate state estimation even in challenging visual conditions. RRxIO c
Service for working with open data of the State Duma of the Russian Federation
Сервис для работы с открытыми данными Госдумы РФ Исходные данные из API Госдумы РФ извлекаются с помощью Apache Nifi и приземляются в хранилище Clickh
DeepLab is a state-of-art deep learning system for semantic image segmentation built on top of Caffe.
DeepLab Introduction DeepLab is a state-of-art deep learning system for semantic image segmentation built on top of Caffe. It combines densely-compute
Source code for our paper "Empathetic Response Generation with State Management"
Source code for our paper "Empathetic Response Generation with State Management" this repository is maintained by both Jun Gao and Yuhan Liu Model Ove
Implementation of the state of the art beat-detection, downbeat-detection and tempo-estimation model
The ISMIR 2020 Beat Detection, Downbeat Detection and Tempo Estimation Model Implementation. This is an implementation in TensorFlow to implement the
State-to-Distribution (STD) Model
State-to-Distribution (STD) Model In this repository we provide exemplary code on how to construct and evaluate a state-to-distribution (STD) model fo
Discord RPC Generator With Python
Discord-RPC-Generator Thank you for using this Discord Custom RP Generator. This is 100% safe and open source. Download Discord for your computer here
A curated list of the latest breakthroughs in AI by release date with a clear video explanation, link to a more in-depth article, and code.
A curated list of the latest breakthroughs in AI by release date with a clear video explanation, link to a more in-depth article, and code
Controller state monitor plugin for EVA ICS
eva-plugin-cmon Controller status monitor plugin for EVA ICS Monitors connected controllers status in SFA and pushes measurements into an external Inf
Sequence Modeling with Structured State Spaces
Structured State Spaces for Sequence Modeling This repository provides implementations and experiments for the following papers. S4 Efficiently Modeli
Sequence Modeling with Structured State Spaces
Structured State Spaces for Sequence Modeling This repository provides implementations and experiments for the following papers. S4 Efficiently Modeli
In this tutorial, raster models of soil depth and soil water holding capacity for the United States will be sampled at random geographic coordinates within the state of Colorado.
Raster_Sampling_Demo (Resulting graph of this demo) Background Sampling values of a raster at specific geographic coordinates can be done with a numbe
Bayes-Newton—A Gaussian process library in JAX, with a unifying view of approximate Bayesian inference as variants of Newton's algorithm.
Bayes-Newton Bayes-Newton is a library for approximate inference in Gaussian processes (GPs) in JAX (with objax), built and actively maintained by Wil
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
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
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
🤗 Transformers: State-of-the-art Natural Language Processing for Pytorch, TensorFlow, and JAX.
English | 简体中文 | 繁體中文 | 한국어 State-of-the-art Natural Language Processing for Jax, PyTorch and TensorFlow 🤗 Transformers provides thousands of pretrai
LWCC: A LightWeight Crowd Counting library for Python that includes several pretrained state-of-the-art models.
LWCC: A LightWeight Crowd Counting library for Python LWCC is a lightweight crowd counting framework for Python. It wraps four state-of-the-art models
Deepparse is a state-of-the-art library for parsing multinational street addresses using deep learning
Here is deepparse. Deepparse is a state-of-the-art library for parsing multinational street addresses using deep learning. Use deepparse to Use the pr
Train a state-of-the-art yolov3 object detector from scratch!
TrainYourOwnYOLO: Building a Custom Object Detector from Scratch This repo let's you train a custom image detector using the state-of-the-art YOLOv3 c
Just RESTing
petnica-api-workshop Just RESTing Setup Using pipenv You can setup this project with pipenv if you want isolated libraries. After you've installed pip
The PyTorch re-implement of a 3D CNN Tracker to extract coronary artery centerlines with state-of-the-art (SOTA) performance. (paper: 'Coronary artery centerline extraction in cardiac CT angiography using a CNN-based orientation classifier')
The PyTorch re-implement of a 3D CNN Tracker to extract coronary artery centerlines with state-of-the-art (SOTA) performance. (paper: 'Coronary artery centerline extraction in cardiac CT angiography using a CNN-based orientation classifier')
State of the Art Neural Networks for Generative Deep Learning
pyradox-generative State of the Art Neural Networks for Generative Deep Learning Table of Contents pyradox-generative Table of Contents Installation U
Propose a principled and practically effective framework for unsupervised accuracy estimation and error detection tasks with theoretical analysis and state-of-the-art performance.
Detecting Errors and Estimating Accuracy on Unlabeled Data with Self-training Ensembles This project is for the paper: Detecting Errors and Estimating