ensemble

Fast and flexible AutoML with learning guarantees.

Python package for AutoML on Tabular Data with Feature Engineering, Hyper-Parameters Tuning, Explanations and Automatic Documentation

Tool for smooth git handover.

A unified ensemble framework for PyTorch to improve the performance and robustness of your deep learning model.

We present MocapNET, a real-time method that estimates the 3D human pose directly in the popular Bio Vision Hierarchy (BVH) format, given estimations of the 2D body joints originating from monocular color images. Our contributions include: (a) A novel and compact 2D pose NSRM representation. (b) A human body orientation classifier and an ensemble of orientation-tuned neural networks that regress the 3D human pose by also allowing for the decomposition of the body to an upper and lower kinematic hierarchy. This permits the recovery of the human pose even in the case of significant occlusions. (c) An efficient Inverse Kinematics solver that refines the neural-network-based solution providing 3D human pose estimations that are consistent with the limb sizes of a target person (if known). All the above yield a 33% accuracy improvement on the Human 3.6 Million (H3.6M) dataset compared to the baseline method (MocapNET) while maintaining real-time performance

ML-Ensemble – high performance ensemble learning

Python package for stacking (machine learning technique)

NLP in Python with Deep Learning

Deep Learning ❤️ PyTorch

🛠️ Class-imbalanced Ensemble Learning Toolbox. | 类别不平衡/长尾机器学习库

Video Face Manipulation Detection Through Ensemble of CNNs

[ICDE'20] ⚖️ A general, efficient ensemble framework for imbalanced classification. | 泛用，高效，鲁棒的类别不平衡学习框架

numpy 实现的 周志华《机器学习》书中的算法及其他一些传统机器学习算法

Deep fusion project of deeply-fused nets, and the study on the connection to ensembling

Stacked Generalization (Ensemble Learning)

The official implementation of "The Shapley Value of Classifiers in Ensemble Games" (CIKM 2021).

[CVPR 2024 Oral, Best Paper Award Candidate] Official repository of "PaSCo: Urban 3D Panoptic Scene Completion with Uncertainty Awareness"

Snapshot Ensembles in Torch (Snapshot Ensembles: Train 1, Get M for Free)

This repository contains the code used in the paper: A high-resolution canopy height model of the Earth. Here, we developed a model to estimate canopy top height anywhere on Earth. The model estimates canopy top height for every Sentinel-2 image pixel and was trained using sparse GEDI LIDAR data as a reference.