Python Hierarchical-state-machine Resources

MultiModal-InfoMax This repository contains the official implementation code of the paper Improving Multimodal Fusion with Hierarchical Mutual Informa

Simple Keyword Clusterer A simple machine learning package to cluster keywords in higher-level groups. Example: "Senior Frontend Engineer" -- "Fronte

Fast Transformer This repo implements Fastformer: Additive Attention Can Be All You Need by Wu et al. in TensorFlow. Fast Transformer is a Transformer

This is a machine learning model deployment project of Iris classification model in a minimal UI using flask web framework and deployed it in Azure cloud using Azure app service. We initially made this project as a requirement for an internship at Indian Servers. We are now making it open to contribution.

PaddlePaddle Vision Transformers State-of-the-art Visual Transformer and MLP Models for PaddlePaddle 🤖 PaddlePaddle Visual Transformers (PaddleViT or

Perceiver IO Unofficial implementation of Perceiver IO: A General Architecture for Structured Inputs & Outputs Usage import torch from src.perceiver.

Codebase for training transformers on systematic generalization datasets. The official repository for our EMNLP 2021 paper The Devil is in the Detail:

Hierarchical Conditional Flow: A Unified Framework for Image Super-Resolution and Image Rescaling (HCFlow, ICCV2021) This repository is the official P

CARLA - Counterfactual And Recourse Library CARLA is a python library to benchmark counterfactual explanation and recourse models. It comes out-of-the

GraphGT: Machine Learning Datasets for Graph Generation and Transformation Dataset Website | Paper Installation Using pip To install the core environm

Hierarchical Conditional Flow: A Unified Framework for Image Super-Resolution and Image Rescaling (HCFlow, ICCV2021) This repository is the official P

Warp Warp brings EVM compatible languages to StarkNet, making it possible to transpile Ethereum smart contracts to Cairo, and use them on StarkNet. Ta

Robust Video Matting in PyTorch, TensorFlow, TensorFlow.js, ONNX, CoreML!

Neural Turing Machine (NTM) & Differentiable Neural Computer (DNC) with pytorch & visdom Sample on-line plotting while training(avg loss)/testing(writ

FreezeOut A simple technique to accelerate neural net training by progressively freezing layers. This repository contains code for the extended abstra

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

fmpytorch A library for factorization machines in pytorch. A factorization machine is like a linear model, except multiplicative interaction terms bet

Scripts to automatically detect obfuscated code and state machines in binaries.

🔧 What is it? Wrench is a benchmark platform containing diverse weak supervision tasks. It also provides a common and easy framework for development

Alias-Free GAN An unofficial version of Alias-Free Generative Adversarial Networks (https://arxiv.org/abs/2106.12423). This repository was heavily bas

A typical datarootsian consumes high-quality fresh coffee in their office environment. The board of dataroots had a very critical decision by the end of 2021-Q2 regarding coffee consumption.

Simple logging of statistics, model checkpoints, plots and other objects for your Machine Learning Experiments (MLE). Furthermore, the MLELogger comes with smooth multi-seed result aggregation and combination of multi-configuration runs. For a quickstart checkout the notebook blog 🚀

TF Watcher TF Watcher is a simple to use Python package and web app which allows you to monitor 👀 your Machine Learning training or testing process o

Text Classification Baseline Pipeline for fast building text classification TF-IDF + LogReg baselines. Usage Instead of writing custom code for specif

A deep learning library for spiking neural networks. Norse aims to exploit the advantages of bio-inspired neural components, which are sparse and even

State Entropy Maximization with Random Encoders for Efficient Exploration (RE3) (ICML 2021) Code for State Entropy Maximization with Random Encoders f

This is code repo for our EMNLP 2017 paper "Reinforcement Learning for Bandit Neural Machine Translation with Simulated Human Feedback", which implements the A2C algorithm on top of a neural encoder-decoder model and benchmarks the combination under simulated noisy rewards.

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.

Detect the programming language of a source code

The goal of this project is to create a learning based system that takes an image of a math formula and returns corresponding LaTeX code.

Framework overview This library allows to quickly implement different architectures based on Reservoir Computing (the family of approaches popularized

R2D2 This is the official code for paper titled "R2D2: Recursive Transformer based on Differentiable Tree for Interpretable Hierarchical Language Mode

Summary Explorer Summary Explorer is a tool to visually inspect the summaries from several state-of-the-art neural summarization models across multipl

Apple NeuralHash is a perceptual hashing method for images based on neural networks. It can tolerate image resize and compression.

Contrastive Learning of Object Representations Supervisor: Prof. Dr. Gemma Roig Institutions: Goethe University CVAI - Computational Vision & Artifici

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.

Query Selector Here you can find code and data loaders for the paper https://arxiv.org/pdf/2107.08687v1.pdf . Query Selector is a novel approach to sp

New State-of-the-Art in Preposition Sense Disambiguation Supervisor: Prof. Dr. Alexander Mehler Alexander Henlein Institutions: Goethe University TTLa

------ 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

This repo is the official implementation of our paper "Instance Adaptive Self-training for Unsupervised Domain Adaptation". The purpose of this repo is to better communicate with you and respond to your questions. This repo is almost the same with Another-Version, and you can also refer to that version.

An Effective Loss Function for Generating 3D Models from Single 2D Image without Rendering Papers with code | Paper Nikola Zubić Pietro Lio University

Marius Marius is a system under active development for training embeddings for large-scale graphs on a single machine. Training on large scale graphs

ACSC Automatic extrinsic calibration for non-repetitive scanning solid-state LiDAR and camera systems. System Architecture 1. Dependency Tested with U

Note: This is an alpha (preview) version which is still under refining. nn-Meter is a novel and efficient system to accurately predict the inference l

Stochastic CSLR This is the PyTorch implementation for the ECCV 2020 paper: Stochastic Fine-grained Labeling of Multi-state Sign Glosses for Continuou

transformer-slt This repository gathers data and code supporting the experiments in the paper Better Sign Language Translation with STMC-Transformer.

A powerful and flexible machine learning platform for drug discovery

A DNN inference latency prediction toolkit for accurately modeling and predicting the latency on diverse edge devices.

Genalog is an open source, cross-platform python package allowing generation of synthetic document images with custom degradations and text alignment capabilities.

Sum-Product Probabilistic Language SPPL is a probabilistic programming language that delivers exact solutions to a broad range of probabilistic infere

Contrastive Learning for Many-to-many Multilingual Neural Machine Translation(mCOLT/mRASP2), ACL2021 The code for training mCOLT/mRASP2, a multilingua

This project is made to help you scale from a basic Machine Learning project for research purposes to a production grade Machine Learning web service

This handbook accompanies the course: Machine Learning with Hung-Yi Lee

PyGCL is an open-source library for graph contrastive learning (GCL), which features modularized GCL components from published papers, standardized evaluation, and experiment management.

ThinkTwice ThinkTwice is a retriever-reader architecture for solving long-text machine reading comprehension. It is based on the paper: ThinkTwice: A

SG-NLP Machine learning models from Singapore's natural language processing (NLP) research community. sgnlp is a Python package that allows you to eas

Causal Inference and Machine Learning in Practice with EconML and CausalML: Industrial Use Cases at Microsoft, TripAdvisor, Uber

ml4h is a toolkit for machine learning on clinical data of all kinds including genetics, labs, imaging, clinical notes, and more

H3DS Dataset This repository contains the code for using the H3DS dataset introduced in H3D-Net: Few-Shot High-Fidelity 3D Head Reconstruction Access

Leetcode compensations report Scraping and analysis of leetcode-compensations page.

CSL-YOLO: A New Lightweight Object Detection System for Edge Computing This project provides a SOTA level lightweight YOLO called "Cross-Stage Lightwe

PyGCL: Graph Contrastive Learning for PyTorch PyGCL is an open-source library for graph contrastive learning (GCL), which features modularized GCL com

Hierarchical Metadata-Aware Document Categorization under Weak Supervision This project provides a weakly supervised framework for hierarchical metada

Convert images of LaTex math equations into LaTex code.

An Introduction to Deep Learning for the Physical Layer An usable PyTorch implementation of the noisy autoencoder infrastructure in the paper "An Intr

Deep CORAL A PyTorch implementation of 'Deep CORAL: Correlation Alignment for Deep Domain Adaptation. B Sun, K Saenko, ECCV 2016' Deep CORAL can learn

xeasy-ml 1. What is xeasy-ml Xeasy-ml is a packaged machine learning framework. It allows a beginner to quickly build a machine learning model and use

HiFT: Hierarchical Feature Transformer for Aerial Tracking Ziang Cao, Changhong Fu, Junjie Ye, Bowen Li, and Yiming Li Our paper is Accepted by ICCV 2

背景 安装教程 快速上手 （一）预训练模型 （二）机器翻译 （三）文本分类 TenTrans 进阶 1. 多语言机器翻译 2. 跨语言预训练 背景 TrenTrans是一个统一的端到端的多语言多任务预训练平台，支持多种预训练方式，以及序列生成和自然语言理解任务。 安装教程 git clone git

Evidently helps analyze machine learning models during validation or production monitoring. The tool generates interactive visual reports and JSON profiles from pandas DataFrame or csv files. Currently 6 reports are available.

🤖 Interactive Machine Learning experiments: 🏋️models training + 🎨models demo

Interpretable Machine Learning with Python, published by Packt

Dynamic Routing Between Capsules - PyTorch implementation PyTorch implementation of NIPS 2017 paper Dynamic Routing Between Capsules from Sara Sabour,

Poincaré Embeddings for Learning Hierarchical Representations PyTorch implementation of Poincaré Embeddings for Learning Hierarchical Representations

Visual-Interaction-Networks An implementation of Deepmind visual interaction networks in Pytorch. Introduction For the purpose of understanding the ch

NIMA: Neural IMage Assessment This is a PyTorch implementation of the paper NIMA: Neural IMage Assessment (accepted at IEEE Transactions on Image Proc

PyTorch Dilated Recurrent Neural Networks PyTorch implementation of Dilated Recurrent Neural Networks (DilatedRNN). Getting Started Installation: $ pi

PyTorch NIMA: Neural IMage Assessment PyTorch implementation of Neural IMage Assessment by Hossein Talebi and Peyman Milanfar. You can learn more from

Non-Autoregressive Transformer Code release for Non-Autoregressive Neural Machine Translation by Jiatao Gu, James Bradbury, Caiming Xiong, Victor O.K.

Deepvoice3_pytorch PyTorch implementation of convolutional networks-based text-to-speech synthesis models: arXiv:1710.07654: Deep Voice 3: Scaling Tex

The revolutionary IDE for all NLP (Natural language processing) stuffs on the internet.

TensorFlow Ranking is a library for Learning-to-Rank (LTR) techniques on the TensorFlow platform

Pandas Machine Learning and Quant Finance Library Collection

H-Transformer-1D Implementation of H-Transformer-1D, Transformer using hierarchical Attention for sequence learning with subquadratic costs. For now,

⭐ [NEW] ⭐ T2F - 2.0 Teaser (coming soon ...) Please note that all the faces in the above samples are generated ones. The T2F 2.0 will be using MSG-GAN

ReSSL: Relational Self-Supervised Learning with Weak Augmentation This repository contains PyTorch evaluation code, training code and pretrained model

CobraML: Completely Customizable What is it? CobraML is a python library built on both numpy and numba. Unlike other ML libraries CobraML gives the us

MUSE stands for Multilingual Universal Sentence Encoder - multilingual extension (supports 16 languages) of Universal Sentence Encoder (USE).

IDRLnet IDRLnet is a machine learning library on top of PyTorch. Use IDRLnet if you need a machine learning library that solves both forward and inver

Voice2Series-Reprogramming Voice2Series: Reprogramming Acoustic Models for Time Series Classification International Conference on Machine Learning (IC

Towards Understanding and Mitigating Social Biases in Language Models This repo contains code and data for evaluating and mitigating bias from generat

This repository is a toolkit to do machine learning for programming languages. It implements tokenization, dataset preprocessing, model training and m

neraug This python library helps you with augmenting text data for named entity recognition. Augmentation Example Reference from An Analysis of Simple

AlphaFold This package provides an implementation of the inference pipeline of AlphaFold v2.0. This is a completely new model that was entered in CASP

This library was developed in order to facilitate rapid prototyping in Python of predictive machine-learning models using longitudinal medical data from an OMOP CDM-standard database.

NeuralCompression is a Python repository dedicated to research of neural networks that compress data. The repository includes tools such as JAX-based entropy coders, image compression models, video compression models, and metrics for image and video evaluation.

A simple tool for explore your object detection dataset. The goal of this library is to provide simple and intuitive visualizations from your dataset and automatically find the best parameters for generating a specific grid of anchors that can fit you data characteristics

A PyTorch Reproduction of HCN Co-occurrence Feature Learning from Skeleton Data for Action Recognition and Detection with Hierarchical Aggregation. Ch

Transparency-by-Design networks (TbD-nets) This repository contains code for replicating the experiments and visualizations from the paper Transparenc