280 Repositories
Python sequence-to-tree Libraries
SPTAG: A library for fast approximate nearest neighbor search
SPTAG: A library for fast approximate nearest neighbor search SPTAG SPTAG (Space Partition Tree And Graph) is a library for large scale vector approxi
Code for "Semantic Role Labeling as Dependency Parsing: Exploring Latent Tree Structures Inside Arguments".
Code for "Semantic Role Labeling as Dependency Parsing: Exploring Latent Tree Structures Inside Arguments".
Constituency Tree Labeling Tool
Constituency Tree Labeling Tool The purpose of this package is to solve the constituency tree labeling problem. Look from the dataset labeled by NLTK,
Fast algorithms to compute an approximation of the minimal volume oriented bounding box of a point cloud in 3D.
ApproxMVBB Status Build UnitTests Homepage Fast algorithms to compute an approximation of the minimal volume oriented bounding box of a point cloud in
A package to predict protein inter-residue geometries from sequence data
trRosetta This package is a part of trRosetta protein structure prediction protocol developed in: Improved protein structure prediction using predicte
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
Scikit-Garden or skgarden is a garden for Scikit-Learn compatible decision trees and forests.
Scikit-Garden or skgarden (pronounced as skarden) is a garden for Scikit-Learn compatible decision trees and forests.
🌲 Implementation of the Robust Random Cut Forest algorithm for anomaly detection on streams
🌲 Implementation of the Robust Random Cut Forest algorithm for anomaly detection on streams
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
Blender pluggin (python script) that adds a randomly generated tree with random branches and bend orientations
Blender pluggin (python script) that adds a randomly generated tree with random branches and bend orientations
Code for the paper "Offline Reinforcement Learning as One Big Sequence Modeling Problem"
Trajectory Transformer Code release for Offline Reinforcement Learning as One Big Sequence Modeling Problem. Installation All python dependencies are
A music recommendation REST API which makes a machine learning algorithm work with the Django REST Framework
music-recommender-rest-api A music recommendation REST API which makes a machine learning algorithm work with the Django REST Framework How it works T
generate-2D-quadrilateral-mesh-with-neural-networks-and-tree-search
generate-2D-quadrilateral-mesh-with-neural-networks-and-tree-search This repository contains single-threaded TreeMesh code. I'm Hua Tong, a senior stu
Implementation of Sequence Generative Adversarial Nets with Policy Gradient
SeqGAN Requirements: Tensorflow r1.0.1 Python 2.7 CUDA 7.5+ (For GPU) Introduction Apply Generative Adversarial Nets to generating sequences of discre
ReGAN: Sequence GAN using RE[INFORCE|LAX|BAR] based PG estimators
Sequence Generation with GANs trained by Gradient Estimation Requirements: PyTorch v0.3 Python 3.6 CUDA 9.1 (For GPU) Origin The idea is from paper Se
Non-Metric Space Library (NMSLIB): An efficient similarity search library and a toolkit for evaluation of k-NN methods for generic non-metric spaces.
Non-Metric Space Library (NMSLIB) Important Notes NMSLIB is generic but fast, see the results of ANN benchmarks. A standalone implementation of our fa
Sequence to Sequence (seq2seq) Recurrent Neural Network (RNN) for Time Series Forecasting
Sequence to Sequence (seq2seq) Recurrent Neural Network (RNN) for Time Series Forecasting Note: You can find here the accompanying seq2seq RNN forecas
An implementation of a sequence to sequence neural network using an encoder-decoder
Keras implementation of a sequence to sequence model for time series prediction using an encoder-decoder architecture. I created this post to share a
A socket script to obtain chinese phones-sequence for any english word
Foreign Pronunciation Generator (English-Chinese) We provide a simple socket script for acquiring Chinese pronunciation of English words (phones in ai
Responsible Machine Learning with Python
Examples of techniques for training interpretable ML models, explaining ML models, and debugging ML models for accuracy, discrimination, and security.
A clean implementation based on AlphaZero for any game in any framework + tutorial + Othello/Gobang/TicTacToe/Connect4 and more
Alpha Zero General (any game, any framework!) A simplified, highly flexible, commented and (hopefully) easy to understand implementation of self-play
Implementation of H-Transformer-1D, Hierarchical Attention for Sequence Learning using 🤗 transformers
hierarchical-transformer-1d Implementation of H-Transformer-1D, Hierarchical Attention for Sequence Learning using 🤗 transformers In Progress!! 2021.
Pulse sequence builder and compiler for q1asm
q1pulse Pulse sequence builder and compiler for q1asm. q1pulse is a simple library to compile pulse sequence to q1asm, the assembly language of Qblox
Platform Tree for Xiaomi Redmi Note 7/7S (lavender)
The Xiaomi Redmi Note 7 (codenamed "lavender") is a mid-range smartphone from Xiaomi announced in January 2019. Device specifications Device Xiaomi Re
Multi-objective constrained optimization for energy applications via tree ensembles
Multi-objective constrained optimization for energy applications via tree ensembles
This repo holds codes of the ICCV21 paper: Visual Alignment Constraint for Continuous Sign Language Recognition.
VAC_CSLR This repo holds codes of the paper: Visual Alignment Constraint for Continuous Sign Language Recognition.(ICCV 2021) [paper] Prerequisites Th
A simple python program that draws a tree for incrementing values using the Collatz Conjecture.
Collatz Conjecture A simple python program that draws a tree for incrementing values using the Collatz Conjecture. Values which can be edited: Length
Test symmetries with sklearn decision tree models
Test symmetries with sklearn decision tree models Setup Begin from an environment with a recent version of python 3. source setup.sh Leave the enviro
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
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
These scripts look for non-printable unicode characters in all text files in a source tree
find-unicode-control These scripts look for non-printable unicode characters in all text files in a source tree. find_unicode_control.py should work w
Decision Border Visualizer for Classification Algorithms
dbv Decision Border Visualizer for Classification Algorithms Project description A python package for Machine Learning Engineers who want to visualize
A simple python implementation of Decision Tree.
DecisionTree A simple python implementation of Decision Tree, using Gini index. Usage: import DecisionTree node = DecisionTree.trainDecisionTree(lab
A PyTorch Implementation of Gated Graph Sequence Neural Networks (GGNN)
A PyTorch Implementation of GGNN This is a PyTorch implementation of the Gated Graph Sequence Neural Networks (GGNN) as described in the paper Gated G
Code for Generating Disentangled Arguments with Prompts: A Simple Event Extraction Framework that Works
GDAP Code for Generating Disentangled Arguments with Prompts: A Simple Event Extraction Framework that Works Environment Python (verified: v3.8) CUDA
Convolutional Recurrent Neural Network (CRNN) for image-based sequence recognition.
Convolutional Recurrent Neural Network This software implements the Convolutional Recurrent Neural Network (CRNN), a combination of CNN, RNN and CTC l
2021 CCF BDCI 全国信息检索挑战杯(CCIR-Cup)智能人机交互自然语言理解赛道第二名参赛解决方案
2021 CCF BDCI 全国信息检索挑战杯(CCIR-Cup) 智能人机交互自然语言理解赛道第二名解决方案 比赛网址: CCIR-Cup-智能人机交互自然语言理解 1.依赖环境: python==3.8 torch==1.7.1+cu110 numpy==1.19.2 transformers=
This app finds duplicate to near duplicate images by generating a hash value for each image stored with a specialized data structure called VP-Tree which makes searching an image on a dataset of 100Ks almost instantanious
Offline Reverse Image Search Overview This app finds duplicate to near duplicate images by generating a hash value for each image stored with a specia
Pytorch implementation of the paper Progressive Growing of Points with Tree-structured Generators (BMVC 2021)
PGpoints Pytorch implementation of the paper Progressive Growing of Points with Tree-structured Generators (BMVC 2021) Hyeontae Son, Young Min Kim Pre
This repository includes the code of the sequence-to-sequence model for discontinuous constituent parsing described in paper Discontinuous Grammar as a Foreign Language.
Discontinuous Grammar as a Foreign Language This repository includes the code of the sequence-to-sequence model for discontinuous constituent parsing
An End-to-End Trainable Neural Network for Image-based Sequence Recognition and Its Application to Scene Text Recognition
CRNN paper:An End-to-End Trainable Neural Network for Image-based Sequence Recognition and Its Application to Scene Text Recognition 1. create your ow
Stochastic Gradient Trees implementation in Python
Stochastic Gradient Trees - Python Stochastic Gradient Trees1 by Henry Gouk, Bernhard Pfahringer, and Eibe Frank implementation in Python. Based on th
Extremely simple and fast extreme multi-class and multi-label classifiers.
napkinXC napkinXC is an extremely simple and fast library for extreme multi-class and multi-label classification, that focus of implementing various m
A Real-Time-Strategy game for Deep Learning research
Description DeepRTS is a high-performance Real-TIme strategy game for Reinforcement Learning research. It is written in C++ for performance, but provi
Individual Tree Crown classification on WorldView-2 Images using Autoencoder -- Group 9 Weak learners - Final Project (Machine Learning 2020 Course)
Created by Olga Sutyrina, Sarah Elemili, Abduragim Shtanchaev and Artur Bille Individual Tree Crown classification on WorldView-2 Images using Autoenc
Facebook AI Research Sequence-to-Sequence Toolkit written in Python.
Fairseq(-py) is a sequence modeling toolkit that allows researchers and developers to train custom models for translation, summarization, language mod
A graph-to-sequence model for one-step retrosynthesis and reaction outcome prediction.
Graph2SMILES A graph-to-sequence model for one-step retrosynthesis and reaction outcome prediction. 1. Environmental setup System requirements Ubuntu:
ALL Snow Removed: Single Image Desnowing Algorithm Using Hierarchical Dual-tree Complex Wavelet Representation and Contradict Channel Loss (HDCWNet)
ALL Snow Removed: Single Image Desnowing Algorithm Using Hierarchical Dual-tree Complex Wavelet Representation and Contradict Channel Loss (HDCWNet) (
Draw tree diagrams from indented text input
Draw tree diagrams This repository contains two very different scripts to produce hierarchical tree diagrams like this one: $ ./classtree.py collectio
Source code for CAST - Crisis Domain Adaptation Using Sequence-to-sequence Transformers (Accepted to ISCRAM 2021, CorePaper).
Source code for CAST: Crisis Domain Adaptation UsingSequence-to-sequenceTransformers (Paper, BibTeX, Accepted to ISCRAM 2021, CorePaper) Quick start D
Source code for The Power of Many: A Physarum Swarm Steiner Tree Algorithm
Physarum-Swarm-Steiner-Algo Source code for The Power of Many: A Physarum Steiner Tree Algorithm Code implements ideas from the following papers: Sher
Hypernets: A General Automated Machine Learning framework to simplify the development of End-to-end AutoML toolkits in specific domains.
A General Automated Machine Learning framework to simplify the development of End-to-end AutoML toolkits in specific domains.
An easy-to-use high-performance asynchronous web framework.
中文 | English 一个易用的高性能异步 web 框架。 Index.py 文档 Index.py 实现了 ASGI3 接口,并使用 Radix Tree 进行路由查找。是最快的 Python web 框架之一。一切特性都服务于快速开发高性能的 Web 服务。 大量正确的类型注释 灵活且高效的
PyPI package for scaffolding out code for decision tree models that can learn to find relationships between the attributes of an object.
Decision Tree Writer This package allows you to train a binary classification decision tree on a list of labeled dictionaries or class instances, and
SynNet - synthetic tree generation using neural networks
SynNet This repo contains the code and analysis scripts for our amortized approach to synthetic tree generation using neural networks. Our model can s
CAPITAL: Optimal Subgroup Identification via Constrained Policy Tree Search
CAPITAL: Optimal Subgroup Identification via Constrained Policy Tree Search This repository is the official implementation of CAPITAL: Optimal Subgrou
Repository sharing code and the model for the paper "Rescoring Sequence-to-Sequence Models for Text Line Recognition with CTC-Prefixes"
Rescoring Sequence-to-Sequence Models for Text Line Recognition with CTC-Prefixes Setup virtualenv -p python3 venv source venv/bin/activate pip instal
general-phylomoji: a phylogenetic tree of emoji
general-phylomoji: a phylogenetic tree of emoji
Lark is a parsing toolkit for Python, built with a focus on ergonomics, performance and modularity.
Lark is a parsing toolkit for Python, built with a focus on ergonomics, performance and modularity.
Code for the paper "Ordered Neurons: Integrating Tree Structures into Recurrent Neural Networks"
ON-LSTM This repository contains the code used for word-level language model and unsupervised parsing experiments in Ordered Neurons: Integrating Tree
ULMFiT for Genomic Sequence Data
Genomic ULMFiT This is an implementation of ULMFiT for genomics classification using Pytorch and Fastai. The model architecture used is based on the A
User-friendly, tiny source code searcher written by pure Python.
User-friendly, tiny source code searcher written in pure Python. Example Usages Cat is equivalent in the regular expression as '^Cat$' bor class Cat
pytorch implementation of "Distilling a Neural Network Into a Soft Decision Tree"
Soft-Decision-Tree Soft-Decision-Tree is the pytorch implementation of Distilling a Neural Network Into a Soft Decision Tree, paper recently published
Implementation of Neural Distance Embeddings for Biological Sequences (NeuroSEED) in PyTorch
Neural Distance Embeddings for Biological Sequences Official implementation of Neural Distance Embeddings for Biological Sequences (NeuroSEED) in PyTo
WRENCH: Weak supeRvision bENCHmark
🔧 What is it? Wrench is a benchmark platform containing diverse weak supervision tasks. It also provides a common and easy framework for development
Lingvo is a framework for building neural networks in Tensorflow, particularly sequence models.
Lingvo is a framework for building neural networks in Tensorflow, particularly sequence models.
[ICLR'19] Trellis Networks for Sequence Modeling
TrellisNet for Sequence Modeling This repository contains the experiments done in paper Trellis Networks for Sequence Modeling by Shaojie Bai, J. Zico
Pervasive Attention: 2D Convolutional Networks for Sequence-to-Sequence Prediction
This is a fork of Fairseq(-py) with implementations of the following models: Pervasive Attention - 2D Convolutional Neural Networks for Sequence-to-Se
A Fast Sequence Transducer Implementation with PyTorch Bindings
transducer A Fast Sequence Transducer Implementation with PyTorch Bindings. The corresponding publication is Sequence Transduction with Recurrent Neur
Sequence modeling benchmarks and temporal convolutional networks
Sequence Modeling Benchmarks and Temporal Convolutional Networks (TCN) This repository contains the experiments done in the work An Empirical Evaluati
The GitHub repository for the paper: “Time Series is a Special Sequence: Forecasting with Sample Convolution and Interaction“.
SCINet This is the original PyTorch implementation of the following work: Time Series is a Special Sequence: Forecasting with Sample Convolution and I
Sequence-to-Sequence learning using PyTorch
Seq2Seq in PyTorch This is a complete suite for training sequence-to-sequence models in PyTorch. It consists of several models and code to both train
Tree LSTM implementation in PyTorch
Tree-Structured Long Short-Term Memory Networks This is a PyTorch implementation of Tree-LSTM as described in the paper Improved Semantic Representati
Reinforcement learning models in ViZDoom environment
DoomNet DoomNet is a ViZDoom agent trained by reinforcement learning. The agent is a neural network that outputs a probability of actions given only p
Sequence to Sequence Models with PyTorch
Sequence to Sequence models with PyTorch This repository contains implementations of Sequence to Sequence (Seq2Seq) models in PyTorch At present it ha
Supervised Contrastive Learning for Downstream Optimized Sequence Representations
SupCL-Seq 📖 Supervised Contrastive Learning for Downstream Optimized Sequence representations (SupCS-Seq) accepted to be published in EMNLP 2021, ext
This is the code repository implementing the paper "TreePartNet: Neural Decomposition of Point Clouds for 3D Tree Reconstruction".
TreePartNet This is the code repository implementing the paper "TreePartNet: Neural Decomposition of Point Clouds for 3D Tree Reconstruction". Depende
Print a directory tree structure in your Python code.
directory-structure Print a directory tree structure in your Python code. Download You can simply: pip install directory-structure Or you can also: Cl
Selene is a Python library and command line interface for training deep neural networks from biological sequence data such as genomes.
Selene is a Python library and command line interface for training deep neural networks from biological sequence data such as genomes.
Code for the paper: Sequence-to-Sequence Learning with Latent Neural Grammars
Code for the paper: Sequence-to-Sequence Learning with Latent Neural Grammars
Code for the paper "Reinforcement Learning as One Big Sequence Modeling Problem"
Trajectory Transformer Code release for Reinforcement Learning as One Big Sequence Modeling Problem. Installation All python dependencies are in envir
Implementation of fast algorithms for Maximum Spanning Tree (MST) parsing that includes fast ArcMax+Reweighting+Tarjan algorithm for single-root dependency parsing.
Fast MST Algorithm Implementation of fast algorithms for (Maximum Spanning Tree) MST parsing that includes fast ArcMax+Reweighting+Tarjan algorithm fo
MWPToolkit is a PyTorch-based toolkit for Math Word Problem (MWP) solving.
MWPToolkit is a PyTorch-based toolkit for Math Word Problem (MWP) solving. It is a comprehensive framework for research purpose that integrates popular MWP benchmark datasets and typical deep learning-based MWP algorithms.
Ptorch NLU, a Chinese text classification and sequence annotation toolkit, supports multi class and multi label classification tasks of Chinese long text and short text, and supports sequence annotation tasks such as Chinese named entity recognition, part of speech tagging and word segmentation.
Pytorch-NLU,一个中文文本分类、序列标注工具包,支持中文长文本、短文本的多类、多标签分类任务,支持中文命名实体识别、词性标注、分词等序列标注任务。 Ptorch NLU, a Chinese text classification and sequence annotation toolkit, supports multi class and multi label classification tasks of Chinese long text and short text, and supports sequence annotation tasks such as Chinese named entity recognition, part of speech tagging and word segmentation.
DeepConsensus uses gap-aware sequence transformers to correct errors in Pacific Biosciences (PacBio) Circular Consensus Sequencing (CCS) data.
DeepConsensus DeepConsensus uses gap-aware sequence transformers to correct errors in Pacific Biosciences (PacBio) Circular Consensus Sequencing (CCS)
Instance Segmentation in 3D Scenes using Semantic Superpoint Tree Networks
SSTNet Instance Segmentation in 3D Scenes using Semantic Superpoint Tree Networks(ICCV2021) by Zhihao Liang, Zhihao Li, Songcen Xu, Mingkui Tan, Kui J
Source Code For Template-Based Named Entity Recognition Using BART
Template-Based NER Source Code For Template-Based Named Entity Recognition Using BART Training Training train.py Inference inference.py Corpus ATIS (h
Sequence-to-Sequence learning using PyTorch
Seq2Seq in PyTorch This is a complete suite for training sequence-to-sequence models in PyTorch. It consists of several models and code to both train
Implementation of Token Shift GPT - An autoregressive model that solely relies on shifting the sequence space for mixing
Token Shift GPT Implementation of Token Shift GPT - An autoregressive model that relies solely on shifting along the sequence dimension and feedforwar
Empower Sequence Labeling with Task-Aware Language Model
LM-LSTM-CRF Check Our New NER Toolkit 🚀 🚀 🚀 Inference: LightNER: inference w. models pre-trained / trained w. any following tools, efficiently. Tra
The official code for paper "R2D2: Recursive Transformer based on Differentiable Tree for Interpretable Hierarchical Language Modeling".
R2D2 This is the official code for paper titled "R2D2: Recursive Transformer based on Differentiable Tree for Interpretable Hierarchical Language Mode
Unofficial pytorch implementation for Self-critical Sequence Training for Image Captioning. and others.
An Image Captioning codebase This is a codebase for image captioning research. It supports: Self critical training from Self-critical Sequence Trainin
LightSeq is a high performance training and inference library for sequence processing and generation implemented in CUDA
LightSeq: A High Performance Library for Sequence Processing and Generation
An implementation for `Text2Event: Controllable Sequence-to-Structure Generation for End-to-end Event Extraction`
Text2Event An implementation for Text2Event: Controllable Sequence-to-Structure Generation for End-to-end Event Extraction Please contact Yaojie Lu (@
Code for paper "ASAP-Net: Attention and Structure Aware Point Cloud Sequence Segmentation"
ASAP-Net This project implements ASAP-Net of paper ASAP-Net: Attention and Structure Aware Point Cloud Sequence Segmentation (BMVC2020). Overview We i
An official implementation of the paper Exploring Sequence Feature Alignment for Domain Adaptive Detection Transformers
Sequence Feature Alignment (SFA) By Wen Wang, Yang Cao, Jing Zhang, Fengxiang He, Zheng-jun Zha, Yonggang Wen, and Dacheng Tao This repository is an o
MASS: Masked Sequence to Sequence Pre-training for Language Generation
MASS: Masked Sequence to Sequence Pre-training for Language Generation
A PyTorch Implementation of Gated Graph Sequence Neural Networks (GGNN)
A PyTorch Implementation of GGNN This is a PyTorch implementation of the Gated Graph Sequence Neural Networks (GGNN) as described in the paper Gated G