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Ensemble Learning

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관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/sunshangquan/EnsIR

공식 코드

EnsIR: An Ensemble Algorithm for Image Restoration via Gaussian Mixture Models

https://github.com/swagato-c/bangla-hwcr-present

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Bengali Handwritten Character Classification using Transfer Learning on Deep Convolutional Neural Network

https://github.com/sxkdz/marcel

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Learning Over Molecular Conformer Ensembles: Datasets and Benchmarks

https://github.com/sydney-machine-learning/evolutionary-bagging

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Evolutionary bagging for ensemble learning

https://github.com/sydney-machine-learning/review-classimbalanced-ensemblelearning

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A review of ensemble learning and data augmentation models for class imbalanced problems: combination, implementation and evaluation

https://github.com/sylyoung/DeepTransferEEG

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T-TIME: Test-Time Information Maximization Ensemble for Plug-and-Play BCIs

https://github.com/t-hasegawa-fu/easy-ensemble

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Easy Ensemble: Simple Deep Ensemble Learning for Sensor-Based Human Activity Recognition

https://github.com/takedarts/swgridnet

공식 코드

SwGridNet: A Deep Convolutional Neural Network based on Grid Topology for Image Classification

https://github.com/talhabozkus/digital-cousins-for-ensemble-q-learning

공식 코드

Leveraging Digital Cousins for Ensemble Q-Learning in Large-Scale Wireless Networks

https://github.com/tensorflow/adanet

공식 코드

Improving Neural Architecture Search Image Classifiers via Ensemble Learning

https://github.com/theroyakash/AKHCRNet

공식 코드

AKHCRNet: Bengali Handwritten Character Recognition Using Deep Learning

https://github.com/thibgo/randomscm

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RandomSCM: interpretable ensembles of sparse classifiers tailored for omics data

https://github.com/timudk/SPDENN

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A Discussion on Solving Partial Differential Equations using Neural Networks

https://github.com/tomorrowi6/SGEN-pytorch

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Sequential Gating Ensemble Network for Noise Robust Multi-Scale Face Restoration

https://github.com/unnir/cancelout

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Embedded feature selection in LSTM networks with multi-objective evolutionary ensemble learning for time series forecasting

https://github.com/ushaham/RBMpaper

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A Deep Learning Approach to Unsupervised Ensemble Learning

https://github.com/vanderschaarlab/mlforhealthlabpub

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Synthetic Model Combination: An Instance-wise Approach to Unsupervised Ensemble Learning

https://github.com/vanh17/techqa

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Mitigating Data Scarcity for Large Language Models

https://github.com/vaseline555/superfed

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Connecting Low-Loss Subspace for Personalized Federated Learning

https://github.com/vdvf96/Differentiable_Model_Selection_for_Ensemble_Learning

공식 코드

Differentiable Model Selection for Ensemble Learning

https://github.com/vinuni-vishc/mi-detection-echo

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Ensemble Learning of Myocardial Displacements for Myocardial Infarction Detection in Echocardiography

https://github.com/vita-group/freetickets

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Deep Ensembling with No Overhead for either Training or Testing: The All-Round Blessings of Dynamic Sparsity

https://github.com/vitiugin/elmict

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Unraveling Code-Mixing Patterns in Migration Discourse: Automated Detection and Analysis of Online Conversations on Reddit

https://github.com/wangxb96/eode

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Exhaustive Exploitation of Nature-inspired Computation for Cancer Screening in an Ensemble Manner

https://github.com/wangxiao5791509/Pedestrian-Attribute-Recognition-Paper-List

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Pedestrian Attribute Recognition: A New Benchmark Dataset and A Large Language Model Augmented Framework

https://github.com/wangzhihua520/SemiNCL_IQA

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Semi-Supervised Deep Ensembles for Blind Image Quality Assessment

https://github.com/western-oc2-lab/intrusion-detection-system-using-cnn-and-transfer-learning

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A Transfer Learning and Optimized CNN Based Intrusion Detection System for Internet of Vehicles

https://github.com/wongzhenhao/elgnn

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Ensemble Learning for Graph Neural Networks

https://github.com/xanderjc/synthetic-model-combination

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Synthetic Model Combination: An Instance-wise Approach to Unsupervised Ensemble Learning

https://github.com/xingli1102/BEDs

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BEDS: Bagging ensemble deep segmentation for nucleus segmentation with testing stage stain augmentation

https://github.com/xl-shao/coralconditiondataset

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Deep learning for multi-label classification of coral conditions in the Indo-Pacific via underwater photogrammetry

https://github.com/xqwang14/sms-loss

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Symmetric Multi-Similarity Loss for EPIC-KITCHENS-100 Multi-Instance Retrieval Challenge 2024

https://github.com/yaoching0/clcnet-rethinking-of-ensemble-modeling

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CLCNet: Rethinking of Ensemble Modeling with Classification Confidence Network

https://github.com/yd1008/ts_ensemble_sunspot

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A comparative study of non-deep learning, deep learning, and ensemble learning methods for sunspot number prediction

https://github.com/yixinghuang/deepmedicplus

공식 코드

Deep learning for brain metastasis detection and segmentation in longitudinal MRI data

https://github.com/yumo216/dgekt

공식 코드

DGEKT: A Dual Graph Ensemble Learning Method for Knowledge Tracing

출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.