Papers with Code 아카이브

Ensemble Learning

태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.

전체 기법전체 데이터셋

하위 태스크

0

평가표

1

보존된 평가 기록

1

코드

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

https://github.com/eric-kruger/RForest_EquitiesPredict

Predicting the direction of stock market prices using random forest

https://github.com/farshidrayhanuiu/CUSBoost

CUSBoost: Cluster-based Under-sampling with Boosting for Imbalanced Classification

https://github.com/himanshuladia/signature-recognizer

Writer Independent Offline Signature Recognition Using Ensemble Learning

https://github.com/ilyatrofimov/sftd

Representation Topology Divergence: A Method for Comparing Neural Network Representations

https://github.com/imvishvaraj/ctr_nlp

An Ensemble-based Approach to Click-Through Rate Prediction for Promoted Listings at Etsy

https://github.com/jim-schwoebel/allie

Imbalanced-learn: A Python Toolbox to Tackle the Curse of Imbalanced Datasets in Machine Learning

https://github.com/jmartinezheras/reproduce-stock-market-direction-random-forests

Predicting the direction of stock market prices using random forest

https://github.com/junjun-jiang/RefESR

Ensemble Super-Resolution with A Reference Dataset

https://github.com/jwzhanggy/Graph-Bert

SEGEN: Sample-Ensemble Genetic Evolutional Network Model

https://github.com/konstantinklemmer/spacegan

Augmenting correlation structures in spatial data using deep generative models

https://github.com/learn-ensemble/PY-SUMMA

Unsupervised Evaluation and Weighted Aggregation of Ranked Predictions

https://github.com/learn-ensemble/R-SUMMA

Unsupervised Evaluation and Weighted Aggregation of Ranked Predictions

https://github.com/lightning-uq-box/lightning-uq-box

Masksembles for Uncertainty Estimation

https://github.com/lucamocerino/Binary-Neural-Networks-PyTorch-1.0

TentacleNet: A Pseudo-Ensemble Template for Accurate Binary Convolutional Neural Networks

https://github.com/mahabdoli/Dynamic-Ensemble-Selection-Comparative-Study

Dynamic Ensemble Learning for Credit Scoring: A Comparative Study

https://github.com/malashinroman/least_action

Sparsely ensembled convolutional neural network classifiers via reinforcement learning

https://github.com/microsoft/MT-DNN

Improving Multi-Task Deep Neural Networks via Knowledge Distillation for Natural Language Understanding

https://github.com/nbhusal/Power-System-State-Estimation

Deep Ensemble Learning-based Approach to Real-time Power System State Estimation

https://github.com/nikitabalabin/topdis

Representation Topology Divergence: A Method for Comparing Neural Network Representations

https://github.com/ormandi/gossip-learning-framework

Gossip Learning with Linear Models on Fully Distributed Data

https://github.com/osman-haider/stock-market-prices-prediction-using-RF

Predicting the direction of stock market prices using random forest

https://github.com/qiaotian/VesselSeg

Ensemble of Deep Convolutional Neural Networks for Learning to Detect Retinal Vessels in Fundus Images

https://github.com/r0mer0m/learning_audio_modeling

General audio tagging with ensembling convolutional neural network and statistical features

https://github.com/ramongss/2020-CSF-COVID19

Short-term forecasting COVID-19 cumulative confirmed cases: Perspectives for Brazil

https://github.com/reek129/Environmental-Monitoring-for-Methane-Leak

Development and Evaluation of Ensemble Learning-based Environmental Methane Detection and Intensity Prediction Models

https://github.com/rmadhwal/trustchain-superapp

Gossip Learning with Linear Models on Fully Distributed Data

https://github.com/scikit-learn-contrib/mapie

Conformal prediction interval for dynamic time-series

https://github.com/shaysakazi/MachineLearningFinalProject

Ensemble Genetic Programming

https://github.com/softsys4ai/neural-distiller

Ensemble Knowledge Distillation for Learning Improved and Efficient Networks

https://github.com/teazrq/rlt

On Variance Estimation of Random Forests with Infinite-Order U-statistics

https://github.com/terryum/Deep_Ensemble_CNN_for_Imbalance_Labels

Parkinson's Disease Assessment from a Wrist-Worn Wearable Sensor in Free-Living Conditions: Deep Ensemble Learning and Visualization

https://github.com/tribler/trustchain-superapp

Gossip Learning with Linear Models on Fully Distributed Data

https://github.com/urbanmobility/SGM_mindspore

Supervised Anomaly Detection via Conditional Generative Adversarial Network and Ensemble Active Learning

https://github.com/weizheliu/cross-domain-crowd-counting

Masksembles for Uncertainty Estimation

https://github.com/wongzhenhao/ELGNN

Ensemble Learning for Graph Neural Networks

https://github.com/wpla/Khaidem.etal.2016_Analysis

Predicting the direction of stock market prices using random forest

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