464 Repositories
Python robust-random-cut-forest Libraries
Python and C++ implementation of "MarkerPose: Robust real-time planar target tracking for accurate stereo pose estimation". Accepted at LXCV @ CVPR 2021.
MarkerPose: Robust real-time planar target tracking for accurate stereo pose estimation This is a PyTorch and LibTorch implementation of MarkerPose: a
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.
Forecasting directional movements of stock prices for intraday trading using LSTM and random forest
Forecasting directional movements of stock-prices for intraday trading using LSTM and random-forest https://arxiv.org/abs/2004.10178 Pushpendu Ghosh,
source code the paper Fast and Robust Iterative Closet Point.
Fast-Robust-ICP This repository includes the source code the paper Fast and Robust Iterative Closet Point. Authors: Juyong Zhang, Yuxin Yao, Bailin De
Contains code for the paper "Vision Transformers are Robust Learners".
Vision Transformers are Robust Learners This repository contains the code for the paper Vision Transformers are Robust Learners by Sayak Paul* and Pin
Apache Liminal is an end-to-end platform for data engineers & scientists, allowing them to build, train and deploy machine learning models in a robust and agile way
Apache Liminals goal is to operationalise the machine learning process, allowing data scientists to quickly transition from a successful experiment to an automated pipeline of model training, validation, deployment and inference in production. Liminal provides a Domain Specific Language to build ML workflows on top of Apache Airflow.
This repository contains PyTorch code for Robust Vision Transformers.
This repository contains PyTorch code for Robust Vision Transformers.
(SIGIR2020) “Asymmetric Tri-training for Debiasing Missing-Not-At-Random Explicit Feedback’’
Asymmetric Tri-training for Debiasing Missing-Not-At-Random Explicit Feedback About This repository accompanies the real-world experiments conducted i
An implementation of "Optimal Textures: Fast and Robust Texture Synthesis and Style Transfer through Optimal Transport"
Optex An implementation of Optimal Textures: Fast and Robust Texture Synthesis and Style Transfer through Optimal Transport for TU Delft CS4240. You c
Unsupervised Language Modeling at scale for robust sentiment classification
** DEPRECATED ** This repo has been deprecated. Please visit Megatron-LM for our up to date Large-scale unsupervised pretraining and finetuning code.
ML-powered Loan-Marketer Customer Filtering Engine
In Loan-Marketing business employees are required to call the user's to buy loans of several fields and in several magnitudes. If employees are calling everybody in the network it is also very lengthy and uncertain that most of the customers will buy it. So, there is a very need for a filtering system that segregates the customers who are unlikely to buy loans and the opposite. Loan-Web is visualized and made up on that context.
Code for the paper: Learning Adversarially Robust Representations via Worst-Case Mutual Information Maximization (https://arxiv.org/abs/2002.11798)
Representation Robustness Evaluations Our implementation is based on code from MadryLab's robustness package and Devon Hjelm's Deep InfoMax. For all t
The official implementation of our CVPR 2021 paper - Hybrid Rotation Averaging: A Fast and Robust Rotation Averaging Approach
Graph Optimizer This repo contains the official implementation of our CVPR 2021 paper - Hybrid Rotation Averaging: A Fast and Robust Rotation Averagin
[3DV 2020] PeeledHuman: Robust Shape Representation for Textured 3D Human Body Reconstruction
PeeledHuman: Robust Shape Representation for Textured 3D Human Body Reconstruction International Conference on 3D Vision, 2020 Sai Sagar Jinka1, Rohan
Official PyTorch implementation of "IntegralAction: Pose-driven Feature Integration for Robust Human Action Recognition in Videos", CVPRW 2021
IntegralAction: Pose-driven Feature Integration for Robust Human Action Recognition in Videos Introduction This repo is official PyTorch implementatio
Robust, modular and efficient implementation of advanced Hamiltonian Monte Carlo algorithms
AdvancedHMC.jl AdvancedHMC.jl provides a robust, modular and efficient implementation of advanced HMC algorithms. An illustrative example for Advanced
Cobalt Strike random C2 Profile generator
Random C2 Profile Generator Cobalt Strike random C2 Profile generator Author: Joe Vest (@joevest) This project is designed to generate malleable c2 pr
[PyTorch] Official implementation of CVPR2021 paper "PointDSC: Robust Point Cloud Registration using Deep Spatial Consistency". https://arxiv.org/abs/2103.05465
PointDSC repository PyTorch implementation of PointDSC for CVPR'2021 paper "PointDSC: Robust Point Cloud Registration using Deep Spatial Consistency",
STYLER: Style Factor Modeling with Rapidity and Robustness via Speech Decomposition for Expressive and Controllable Neural Text to Speech
STYLER: Style Factor Modeling with Rapidity and Robustness via Speech Decomposition for Expressive and Controllable Neural Text to Speech Keon Lee, Ky
《Improving Unsupervised Image Clustering With Robust Learning》(2020)
Improving Unsupervised Image Clustering With Robust Learning This repo is the PyTorch codes for "Improving Unsupervised Image Clustering With Robust L
Automated Machine Learning Pipeline with Feature Engineering and Hyper-Parameters Tuning
The mljar-supervised is an Automated Machine Learning Python package that works with tabular data. I
An open source reinforcement learning framework for training, evaluating, and deploying robust trading agents.
TensorTrade: Trade Efficiently with Reinforcement Learning TensorTrade is still in Beta, meaning it should be used very cautiously if used in producti
[ECCVW2020] Robust Long-Term Object Tracking via Improved Discriminative Model Prediction (RLT-DiMP)
Feel free to visit my homepage Robust Long-Term Object Tracking via Improved Discriminative Model Prediction (RLT-DIMP) [ECCVW2020 paper] Presentation
git git《Transformer Meets Tracker: Exploiting Temporal Context for Robust Visual Tracking》(CVPR 2021) GitHub:git2] 《Masksembles for Uncertainty Estimation》(CVPR 2021) GitHub:git3]
Transformer Meets Tracker: Exploiting Temporal Context for Robust Visual Tracking Ning Wang, Wengang Zhou, Jie Wang, and Houqiang Li Accepted by CVPR
PSENet - Shape Robust Text Detection with Progressive Scale Expansion Network.
News Python3 implementations of PSENet [1], PAN [2] and PAN++ [3] are released at https://github.com/whai362/pan_pp.pytorch. [1] W. Wang, E. Xie, X. L
text detection mainly based on ctpn model in tensorflow, id card detect, connectionist text proposal network
text-detection-ctpn Scene text detection based on ctpn (connectionist text proposal network). It is implemented in tensorflow. The origin paper can be
An Implementation of the seglink alogrithm in paper Detecting Oriented Text in Natural Images by Linking Segments
Tips: A more recent scene text detection algorithm: PixelLink, has been implemented here: https://github.com/ZJULearning/pixel_link Contents: Introduc
This is a tensorflow re-implementation of PSENet: Shape Robust Text Detection with Progressive Scale Expansion Network.My blog:
PSENet: Shape Robust Text Detection with Progressive Scale Expansion Network Introduction This is a tensorflow re-implementation of PSENet: Shape Robu
caffe re-implementation of R2CNN: Rotational Region CNN for Orientation Robust Scene Text Detection
R2CNN: Rotational Region CNN for Orientation Robust Scene Text Detection Abstract This is a caffe re-implementation of R2CNN: Rotational Region CNN fo
Back to the Feature: Learning Robust Camera Localization from Pixels to Pose (CVPR 2021)
Back to the Feature with PixLoc We introduce PixLoc, a neural network for end-to-end learning of camera localization from an image and a 3D model via
Code for CVPR2021 paper "Robust Reflection Removal with Reflection-free Flash-only Cues"
Robust Reflection Removal with Reflection-free Flash-only Cues (RFC) Paper | To be released: Project Page | Video | Data Tensorflow implementation for
[CVPR2021] The source code for our paper 《Removing the Background by Adding the Background: Towards Background Robust Self-supervised Video Representation Learning》.
TBE The source code for our paper "Removing the Background by Adding the Background: Towards Background Robust Self-supervised Video Representation Le
BatchFlow helps you conveniently work with random or sequential batches of your data and define data processing and machine learning workflows even for datasets that do not fit into memory.
BatchFlow BatchFlow helps you conveniently work with random or sequential batches of your data and define data processing and machine learning workflo
treeinterpreter - Interpreting scikit-learn's decision tree and random forest predictions.
TreeInterpreter Package for interpreting scikit-learn's decision tree and random forest predictions. Allows decomposing each prediction into bias and
A data-driven approach to quantify the value of classifiers in a machine learning ensemble.
Documentation | External Resources | Research Paper Shapley is a Python library for evaluating binary classifiers in a machine learning ensemble. The
ThunderGBM: Fast GBDTs and Random Forests on GPUs
Documentations | Installation | Parameters | Python (scikit-learn) interface What's new? ThunderGBM won 2019 Best Paper Award from IEEE Transactions o
Home repository for the Regularized Greedy Forest (RGF) library. It includes original implementation from the paper and multithreaded one written in C++, along with various language-specific wrappers.
Regularized Greedy Forest Regularized Greedy Forest (RGF) is a tree ensemble machine learning method described in this paper. RGF can deliver better r
It is a forest of random projection trees
rpforest rpforest is a Python library for approximate nearest neighbours search: finding points in a high-dimensional space that are close to a given
A Python Automated Machine Learning tool that optimizes machine learning pipelines using genetic programming.
Master status: Development status: Package information: TPOT stands for Tree-based Pipeline Optimization Tool. Consider TPOT your Data Science Assista
Little Ball of Fur - A graph sampling extension library for NetworKit and NetworkX (CIKM 2020)
Little Ball of Fur is a graph sampling extension library for Python. Please look at the Documentation, relevant Paper, Promo video and External Resour
Object detection on multiple datasets with an automatically learned unified label space.
Simple multi-dataset detection An object detector trained on multiple large-scale datasets with a unified label space; Winning solution of E
An anthology of a variety of tools for the Persian language in Python
An anthology of a variety of tools for the Persian language in Python
🍊 :bar_chart: :bulb: Orange: Interactive data analysis
Orange Data Mining Orange is a data mining and visualization toolbox for novice and expert alike. To explore data with Orange, one requires no program
Analytics service that is part of iter8. Robust analytics and control to unleash cloud-native continuous experimentation.
iter8-analytics iter8 enables statistically robust continuous experimentation of microservices in your CI/CD pipelines. For in-depth information about
A Robust Non-IoU Alternative to Non-Maxima Suppression in Object Detection
Confluence: A Robust Non-IoU Alternative to Non-Maxima Suppression in Object Detection 1. 介绍 用以替代 NMS,在所有 bbox 中挑选出最优的集合。 NMS 仅考虑了 bbox 的得分,然后根据 IOU 来
Flask-Rebar combines flask, marshmallow, and swagger for robust REST services.
Flask-Rebar Flask-Rebar combines flask, marshmallow, and swagger for robust REST services. Features Request and Response Validation - Flask-Rebar reli
A Bot Which Can generate Random Account Based On Your Hits.
AccountGenBot This Bot Can Generate Account With Hits You Save (Randomly) Keyfeatures Join To Use Support Limit Account Generation Using Sql Customiza
Random scripts and other bits for interacting with the SpaceX Starlink user terminal hardware
starlink-grpc-tools This repository has a handful of tools for interacting with the gRPC service implemented on the Starlink user terminal (AKA "the d
Random Turkish name generator with realistic probabilities.
trnames Random Turkish name generator with realistic probabilities. Based on Trey Hunner's names package. Installation The package can be installed us
ThunderGBM: Fast GBDTs and Random Forests on GPUs
Documentations | Installation | Parameters | Python (scikit-learn) interface What's new? ThunderGBM won 2019 Best Paper Award from IEEE Transactions o
:game_die: Pytest plugin to randomly order tests and control random.seed
pytest-randomly Pytest plugin to randomly order tests and control random.seed. Features All of these features are on by default but can be disabled wi
Flask-Rebar combines flask, marshmallow, and swagger for robust REST services.
Flask-Rebar Flask-Rebar combines flask, marshmallow, and swagger for robust REST services. Features Request and Response Validation - Flask-Rebar reli
An implementation of Deep Forest 2021.2.1.
Deep Forest (DF) 21 DF21 is an implementation of Deep Forest 2021.2.1. It is designed to have the following advantages: Powerful: Better accuracy than
Unadversarial Examples: Designing Objects for Robust Vision
Unadversarial Examples: Designing Objects for Robust Vision This repository contains the code necessary to replicate the major results of our paper: U
a robust room presence solution for home automation with nearly no false negatives
Argos Room Presence This project builds a room presence solution on top of Argos. Using just a cheap raspberry pi zero w (plus an attached pi camera,
The official implementation of NeMo: Neural Mesh Models of Contrastive Features for Robust 3D Pose Estimation [ICLR-2021]. https://arxiv.org/pdf/2101.12378.pdf
NeMo: Neural Mesh Models of Contrastive Features for Robust 3D Pose Estimation [ICLR-2021] Release Notes The offical PyTorch implementation of NeMo, p
🌳 A Python-inspired implementation of the Optimum-Path Forest classifier.
OPFython: A Python-Inspired Optimum-Path Forest Classifier Welcome to OPFython. Note that this implementation relies purely on the standard LibOPF. Th
Automates Machine Learning Pipeline with Feature Engineering and Hyper-Parameters Tuning :rocket:
MLJAR Automated Machine Learning Documentation: https://supervised.mljar.com/ Source Code: https://github.com/mljar/mljar-supervised Table of Contents
A Sklearn-like Framework for Hyperparameter Tuning and AutoML in Deep Learning projects. Finally have the right abstractions and design patterns to properly do AutoML. Let your pipeline steps have hyperparameter spaces. Enable checkpoints to cut duplicate calculations. Go from research to production environment easily.
Neuraxle Pipelines Code Machine Learning Pipelines - The Right Way. Neuraxle is a Machine Learning (ML) library for building machine learning pipeline
Home repository for the Regularized Greedy Forest (RGF) library. It includes original implementation from the paper and multithreaded one written in C++, along with various language-specific wrappers.
Regularized Greedy Forest Regularized Greedy Forest (RGF) is a tree ensemble machine learning method described in this paper. RGF can deliver better r
A Python Automated Machine Learning tool that optimizes machine learning pipelines using genetic programming.
Master status: Development status: Package information: TPOT stands for Tree-based Pipeline Optimization Tool. Consider TPOT your Data Science Assista
Little Ball of Fur - A graph sampling extension library for NetworKit and NetworkX (CIKM 2020)
Little Ball of Fur is a graph sampling extension library for Python. Please look at the Documentation, relevant Paper, Promo video and External Resour
A data-driven approach to quantify the value of classifiers in a machine learning ensemble.
Documentation | External Resources | Research Paper Shapley is a Python library for evaluating binary classifiers in a machine learning ensemble. The
H2O is an Open Source, Distributed, Fast & Scalable Machine Learning Platform: Deep Learning, Gradient Boosting (GBM) & XGBoost, Random Forest, Generalized Linear Modeling (GLM with Elastic Net), K-Means, PCA, Generalized Additive Models (GAM), RuleFit, Support Vector Machine (SVM), Stacked Ensembles, Automatic Machine Learning (AutoML), etc.
H2O H2O is an in-memory platform for distributed, scalable machine learning. H2O uses familiar interfaces like R, Python, Scala, Java, JSON and the Fl