200 Repositories
Python state-lattice-planner Libraries
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
LeLeLe: A tool to simplify the application of Lattice attacks.
LeLeLe is a very simple library (300 lines) to help you more easily implement lattice attacks, the library is inspired by Z3Py (python interfa
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
Django backend of Helium's planner application
Helium Platform Project Prerequisites Python (= 3.6) Pip (= 9.0) MySQL (= 5.7) Redis (= 3.2) Getting Started The Platform is developed using Pytho
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
A course-planning, course-map rendering and GPA-calculation web service, designed for the SFU (Simon Fraser University) student.
SFU Course Planner What is the overall goal of the project (i.e. what does it do, or what problem is it solving)? As the title suggests, this project
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
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
OpenFace – a state-of-the art tool intended for facial landmark detection, head pose estimation, facial action unit recognition, and eye-gaze estimation.
OpenFace 2.2.0: a facial behavior analysis toolkit Over the past few years, there has been an increased interest in automatic facial behavior analysis
Repo for EchoVPR: Echo State Networks for Visual Place Recognition
EchoVPR Repo for EchoVPR: Echo State Networks for Visual Place Recognition Currently under development Dirs: data: pre-collected hidden representation
PyTorch implementation for paper StARformer: Transformer with State-Action-Reward Representations.
StARformer This repository contains the PyTorch implementation for our paper titled StARformer: Transformer with State-Action-Reward Representations.
Fuzzification helps developers protect the released, binary-only software from attackers who are capable of applying state-of-the-art fuzzing techniques
About Fuzzification Fuzzification helps developers protect the released, binary-only software from attackers who are capable of applying state-of-the-
deep-table implements various state-of-the-art deep learning and self-supervised learning algorithms for tabular data using PyTorch.
deep-table implements various state-of-the-art deep learning and self-supervised learning algorithms for tabular data using PyTorch.
Interactive Terraform visualization. State and configuration explorer.
Rover - Terraform Visualizer Rover is a Terraform visualizer. In order to do this, Rover: generates a plan file and parses the configuration in the ro
🤗 Transformers: State-of-the-art Natural Language Processing for Pytorch, TensorFlow, and JAX.
English | 简体中文 | 繁體中文 State-of-the-art Natural Language Processing for Jax, PyTorch and TensorFlow 🤗 Transformers provides thousands of pretrained mo
A script depending on VASP output for calculating Fermi-Softness.
Fermi softness calculation for Vienna Ab initio Simulation Package (VASP) Update 1.1.0: Big update: Rewrote the code. Use Bader atomic division instea
A model library for exploring state-of-the-art deep learning topologies and techniques for optimizing Natural Language Processing neural networks
A Deep Learning NLP/NLU library by Intel® AI Lab Overview | Models | Installation | Examples | Documentation | Tutorials | Contributing NLP Architect
Entropy-controlled contexts in Python
Python module ordered ordered module is the opposite to random - it maintains order in the program. import random x = 5 def increase(): global x
InfraGenie is allows you to split out your infrastructure project into separate independent pieces, each with its own terraform state.
🧞 InfraGenie InfraGenie is allows you to split out your infrastructure project into separate independent pieces, each with its own terraform state. T
PaddleViT: State-of-the-art Visual Transformer and MLP Models for PaddlePaddle 2.0+
PaddlePaddle Vision Transformers State-of-the-art Visual Transformer and MLP Models for PaddlePaddle 🤖 PaddlePaddle Visual Transformers (PaddleViT or
Automatically detect obfuscated code and other state machines
Scripts to automatically detect obfuscated code and state machines in binaries.
RE3: State Entropy Maximization with Random Encoders for Efficient Exploration
State Entropy Maximization with Random Encoders for Efficient Exploration (RE3) (ICML 2021) Code for State Entropy Maximization with Random Encoders f
Local trajectory planner based on a multilayer graph framework for autonomous race vehicles.
Graph-Based Local Trajectory Planner The graph-based local trajectory planner is python-based and comes with open interfaces as well as debug, visuali
IMS-Toucan is a toolkit to train state-of-the-art Speech Synthesis models
IMS-Toucan is a toolkit to train state-of-the-art Speech Synthesis models. Everything is pure Python and PyTorch based to keep it as simple and beginner-friendly, yet powerful as possible.
Library for implementing reservoir computing models (echo state networks) for multivariate time series classification and clustering.
Framework overview This library allows to quickly implement different architectures based on Reservoir Computing (the family of approaches popularized
Summary Explorer is a tool to visually explore the state-of-the-art in text summarization.
Summary Explorer Summary Explorer is a tool to visually inspect the summaries from several state-of-the-art neural summarization models across multipl
FastReID is a research platform that implements state-of-the-art re-identification algorithms.
FastReID is a research platform that implements state-of-the-art re-identification algorithms.
Summary Explorer is a tool to visually explore the state-of-the-art in text summarization.
Summary Explorer is a tool to visually explore the state-of-the-art in text summarization.
Learn meanings behind words is a key element in NLP. This project concentrates on the disambiguation of preposition senses. Therefore, we train a bert-transformer model and surpass the state-of-the-art.
New State-of-the-Art in Preposition Sense Disambiguation Supervisor: Prof. Dr. Alexander Mehler Alexander Henlein Institutions: Goethe University TTLa
😇A pyTorch implementation of the DeepMoji model: state-of-the-art deep learning model for analyzing sentiment, emotion, sarcasm etc
------ Update September 2018 ------ It's been a year since TorchMoji and DeepMoji were released. We're trying to understand how it's being used such t
We evaluate our method on different datasets (including ShapeNet, CUB-200-2011, and Pascal3D+) and achieve state-of-the-art results, outperforming all the other supervised and unsupervised methods and 3D representations, all in terms of performance, accuracy, and training time.
An Effective Loss Function for Generating 3D Models from Single 2D Image without Rendering Papers with code | Paper Nikola Zubić Pietro Lio University
Automatic Calibration for Non-repetitive Scanning Solid-State LiDAR and Camera Systems
ACSC Automatic extrinsic calibration for non-repetitive scanning solid-state LiDAR and camera systems. System Architecture 1. Dependency Tested with U
PyTorch implementation for Stochastic Fine-grained Labeling of Multi-state Sign Glosses for Continuous Sign Language Recognition.
Stochastic CSLR This is the PyTorch implementation for the ECCV 2020 paper: Stochastic Fine-grained Labeling of Multi-state Sign Glosses for Continuou
A state of the art of new lightweight YOLO model implemented by TensorFlow 2.
CSL-YOLO: A New Lightweight Object Detection System for Edge Computing This project provides a SOTA level lightweight YOLO called "Cross-Stage Lightwe
An all-in-one application to visualize multiple different local path planning algorithms
Table of Contents Table of Contents Local Planner Visualization Project (LPVP) Features Installation/Usage Local Planners Probabilistic Roadmap (PRM)
🤗 Transformers: State-of-the-art Natural Language Processing for Pytorch, TensorFlow, and JAX.
English | 简体中文 | 繁體中文 State-of-the-art Natural Language Processing for Jax, PyTorch and TensorFlow 🤗 Transformers provides thousands of pretrained mo
Automated machine learning: Review of the state-of-the-art and opportunities for healthcare
Automated machine learning: Review of the state-of-the-art and opportunities for healthcare
A selection of State Of The Art research papers (and code) on human locomotion (pose + trajectory) prediction (forecasting)
A selection of State Of The Art research papers (and code) on human trajectory prediction (forecasting). Papers marked with [W] are workshop papers.
This is the unofficial code of Deep Dual-resolution Networks for Real-time and Accurate Semantic Segmentation of Road Scenes. which achieve state-of-the-art trade-off between accuracy and speed on cityscapes and camvid, without using inference acceleration and extra data
Deep Dual-resolution Networks for Real-time and Accurate Semantic Segmentation of Road Scenes Introduction This is the unofficial code of Deep Dual-re
Motion Planner Augmented Reinforcement Learning for Robot Manipulation in Obstructed Environments (CoRL 2020)
Motion Planner Augmented Reinforcement Learning for Robot Manipulation in Obstructed Environments [Project website] [Paper] This project is a PyTorch
Code for the paper "Implicit Representations of Meaning in Neural Language Models"
Implicit Representations of Meaning in Neural Language Models Preliminaries Create and set up a conda environment as follows: conda create -n state-pr
A collection of modules I have created to programmatically search for/download imagery from live cam feeds across the state of California.
A collection of modules that I have created to programmatically search for/download imagery from all publicly available live cam feeds across the state of California. In no way am I affiliated with any of these organizations and these modules/methods of gathering imagery are completely unofficial.
State-of-the-art data augmentation search algorithms in PyTorch
MuarAugment Description MuarAugment is a package providing the easiest way to a state-of-the-art data augmentation pipeline. How to use You can instal
Automatic differentiation with weighted finite-state transducers.
GTN: Automatic Differentiation with WFSTs Quickstart | Installation | Documentation What is GTN? GTN is a framework for automatic differentiation with
Model-free Vehicle Tracking and State Estimation in Point Cloud Sequences
Model-free Vehicle Tracking and State Estimation in Point Cloud Sequences 1. Introduction This project is for paper Model-free Vehicle Tracking and St
Deep Text Search is an AI-powered multilingual text search and recommendation engine with state-of-the-art transformer-based multilingual text embedding (50+ languages).
Deep Text Search - AI Based Text Search & Recommendation System Deep Text Search is an AI-powered multilingual text search and recommendation engine w
Pytorch code for "State-only Imitation with Transition Dynamics Mismatch" (ICLR 2020)
This repo contains code for our paper State-only Imitation with Transition Dynamics Mismatch published at ICLR 2020. The code heavily uses the RL mach
TensorFlow Decision Forests (TF-DF) is a collection of state-of-the-art algorithms for the training, serving and interpretation of Decision Forest models.
TensorFlow Decision Forests (TF-DF) is a collection of state-of-the-art algorithms for the training, serving and interpretation of Decision Forest models. The library is a collection of Keras models and supports classification, regression and ranking. TF-DF is a TensorFlow wrapper around the Yggdrasil Decision Forests C++ libraries. Models trained with TF-DF are compatible with Yggdrasil Decision Forests' models, and vice versa.
tsai is an open-source deep learning package built on top of Pytorch & fastai focused on state-of-the-art techniques for time series classification, regression and forecasting.
Time series Timeseries Deep Learning Pytorch fastai - State-of-the-art Deep Learning with Time Series and Sequences in Pytorch / fastai
LaneDet is an open source lane detection toolbox based on PyTorch that aims to pull together a wide variety of state-of-the-art lane detection models
LaneDet is an open source lane detection toolbox based on PyTorch that aims to pull together a wide variety of state-of-the-art lane detection models. Developers can reproduce these SOTA methods and build their own methods.
Incorporating Transformer and LSTM to Kalman Filter with EM algorithm
Deep learning based state estimation: incorporating Transformer and LSTM to Kalman Filter with EM algorithm Overview Kalman Filter requires the true p
pytorch-kaldi is a project for developing state-of-the-art DNN/RNN hybrid speech recognition systems. The DNN part is managed by pytorch, while feature extraction, label computation, and decoding are performed with the kaldi toolkit.
The PyTorch-Kaldi Speech Recognition Toolkit PyTorch-Kaldi is an open-source repository for developing state-of-the-art DNN/HMM speech recognition sys
This is the library for the Unbounded Interleaved-State Recurrent Neural Network (UIS-RNN) algorithm, corresponding to the paper Fully Supervised Speaker Diarization.
UIS-RNN Overview This is the library for the Unbounded Interleaved-State Recurrent Neural Network (UIS-RNN) algorithm. UIS-RNN solves the problem of s
QuickAI is a Python library that makes it extremely easy to experiment with state-of-the-art Machine Learning models.
QuickAI is a Python library that makes it extremely easy to experiment with state-of-the-art Machine Learning models.
QuickAI is a Python library that makes it extremely easy to experiment with state-of-the-art Machine Learning models.
QuickAI is a Python library that makes it extremely easy to experiment with state-of-the-art Machine Learning models.
State of the art Semantic Sentence Embeddings
Contrastive Tension State of the art Semantic Sentence Embeddings Published Paper · Huggingface Models · Report Bug Overview This is the official code
Quickly comparing your image classification models with the state-of-the-art models (such as DenseNet, ResNet, ...)
Image Classification Project Killer in PyTorch This repo is designed for those who want to start their experiments two days before the deadline and ki
Awesome-NLP-Research (ANLP)
Awesome-NLP-Research (ANLP)
Newt - a Gaussian process library in JAX.
Newt __ \/_ (' \`\ _\, \ \\/ /`\/\ \\ \ \\
Code for paper "A Critical Assessment of State-of-the-Art in Entity Alignment" (https://arxiv.org/abs/2010.16314)
A Critical Assessment of State-of-the-Art in Entity Alignment This repository contains the source code for the paper A Critical Assessment of State-of
Visual Automata is a Python 3 library built as a wrapper for Caleb Evans' Automata library to add more visualization features.
Visual Automata Copyright 2021 Lewi Lie Uberg Released under the MIT license Visual Automata is a Python 3 library built as a wrapper for Caleb Evans'
Ocular is a state-of-the-art historical OCR system.
Ocular Ocular is a state-of-the-art historical OCR system. Its primary features are: Unsupervised learning of unknown fonts: requires only document im
TensorFlowTTS: Real-Time State-of-the-art Speech Synthesis for Tensorflow 2 (supported including English, Korean, Chinese, German and Easy to adapt for other languages)
🤪 TensorFlowTTS provides real-time state-of-the-art speech synthesis architectures such as Tacotron-2, Melgan, Multiband-Melgan, FastSpeech, FastSpeech2 based-on TensorFlow 2. With Tensorflow 2, we can speed-up training/inference progress, optimizer further by using fake-quantize aware and pruning, make TTS models can be run faster than real-time and be able to deploy on mobile devices or embedded systems.
SSL_SLAM2: Lightweight 3-D Localization and Mapping for Solid-State LiDAR (mapping and localization separated) ICRA 2021
SSL_SLAM2 Lightweight 3-D Localization and Mapping for Solid-State LiDAR (Intel Realsense L515 as an example) This repo is an extension work of SSL_SL
A very simple framework for state-of-the-art Natural Language Processing (NLP)
A very simple framework for state-of-the-art NLP. Developed by Humboldt University of Berlin and friends. Flair is: A powerful NLP library. Flair allo
DaCy: The State of the Art Danish NLP pipeline using SpaCy
DaCy: A SpaCy NLP Pipeline for Danish DaCy is a Danish preprocessing pipeline trained in SpaCy. At the time of writing it has achieved State-of-the-Ar
Hook and simulate global keyboard events on Windows and Linux.
keyboard Take full control of your keyboard with this small Python library. Hook global events, register hotkeys, simulate key presses and much more.
Named-entity recognition using neural networks. Easy-to-use and state-of-the-art results.
NeuroNER NeuroNER is a program that performs named-entity recognition (NER). Website: neuroner.com. This page gives step-by-step instructions to insta
A model library for exploring state-of-the-art deep learning topologies and techniques for optimizing Natural Language Processing neural networks
A Deep Learning NLP/NLU library by Intel® AI Lab Overview | Models | Installation | Examples | Documentation | Tutorials | Contributing NLP Architect
:mag: End-to-End Framework for building natural language search interfaces to data by utilizing Transformers and the State-of-the-Art of NLP. Supporting DPR, Elasticsearch, HuggingFace’s Modelhub and much more!
Haystack is an end-to-end framework that enables you to build powerful and production-ready pipelines for different search use cases. Whether you want
State of the Art Natural Language Processing
Spark NLP: State of the Art Natural Language Processing Spark NLP is a Natural Language Processing library built on top of Apache Spark ML. It provide
💥 Fast State-of-the-Art Tokenizers optimized for Research and Production
Provides an implementation of today's most used tokenizers, with a focus on performance and versatility. Main features: Train new vocabularies and tok
A very simple framework for state-of-the-art Natural Language Processing (NLP)
A very simple framework for state-of-the-art NLP. Developed by Humboldt University of Berlin and friends. IMPORTANT: (30.08.2020) We moved our models
🤗Transformers: State-of-the-art Natural Language Processing for Pytorch and TensorFlow 2.0.
State-of-the-art Natural Language Processing for PyTorch and TensorFlow 2.0 🤗 Transformers provides thousands of pretrained models to perform tasks o
A disassembler for the RP2040 Programmable I/O State-machine!
piodisasm A disassembler for the RP2040 Programmable I/O State-machine! Usage Just run piodisasm.py on a file that contains the PIO code as hex! (Such
Named-entity recognition using neural networks. Easy-to-use and state-of-the-art results.
NeuroNER NeuroNER is a program that performs named-entity recognition (NER). Website: neuroner.com. This page gives step-by-step instructions to insta
A model library for exploring state-of-the-art deep learning topologies and techniques for optimizing Natural Language Processing neural networks
A Deep Learning NLP/NLU library by Intel® AI Lab Overview | Models | Installation | Examples | Documentation | Tutorials | Contributing NLP Architect
State of the Art Natural Language Processing
Spark NLP: State of the Art Natural Language Processing Spark NLP is a Natural Language Processing library built on top of Apache Spark ML. It provide
💥 Fast State-of-the-Art Tokenizers optimized for Research and Production
Provides an implementation of today's most used tokenizers, with a focus on performance and versatility. Main features: Train new vocabularies and tok
A very simple framework for state-of-the-art Natural Language Processing (NLP)
A very simple framework for state-of-the-art NLP. Developed by Humboldt University of Berlin and friends. IMPORTANT: (30.08.2020) We moved our models
🤗Transformers: State-of-the-art Natural Language Processing for Pytorch and TensorFlow 2.0.
State-of-the-art Natural Language Processing for PyTorch and TensorFlow 2.0 🤗 Transformers provides thousands of pretrained models to perform tasks o
Django friendly finite state machine support
Django friendly finite state machine support django-fsm adds simple declarative state management for django models. If you need parallel task executio
Display machine state using Python3 with Flask.
Flask-State English | 简体中文 Flask-State is a lightweight chart plugin for displaying machine state data in your web application. Monitored Metric: CPU,
Easy to use, state-of-the-art Neural Machine Translation for 100+ languages
EasyNMT - Easy to use, state-of-the-art Neural Machine Translation This package provides easy to use, state-of-the-art machine translation for more th
Command line animations based on the state of the system
shell-emotions Command line animations based on the state of the system for Linux or Windows 10 The ascii animations were created using a modified ver
State of the Art Neural Networks for Deep Learning
pyradox This python library helps you with implementing various state of the art neural networks in a totally customizable fashion using Tensorflow 2
Applications using the GTN library and code to reproduce experiments in "Differentiable Weighted Finite-State Transducers"
gtn_applications An applications library using GTN. Current examples include: Offline handwriting recognition Automatic speech recognition Installing
Reinforcement Learning Coach by Intel AI Lab enables easy experimentation with state of the art Reinforcement Learning algorithms
Coach Coach is a python reinforcement learning framework containing implementation of many state-of-the-art algorithms. It exposes a set of easy-to-us
Named-entity recognition using neural networks. Easy-to-use and state-of-the-art results.
NeuroNER NeuroNER is a program that performs named-entity recognition (NER). Website: neuroner.com. This page gives step-by-step instructions to insta
Easy and comprehensive assessment of predictive power, with support for neuroimaging features
Documentation: https://raamana.github.io/neuropredict/ News As of v0.6, neuropredict now supports regression applications i.e. predicting continuous t
Hook and simulate global keyboard events on Windows and Linux.
keyboard Take full control of your keyboard with this small Python library. Hook global events, register hotkeys, simulate key presses and much more.
A lightweight, object-oriented finite state machine implementation in Python with many extensions
transitions A lightweight, object-oriented state machine implementation in Python with many extensions. Compatible with Python 2.7+ and 3.0+. Installa