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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/nikitadurasov/masksembles

공식 코드

Masksembles for Uncertainty Estimation

https://github.com/nvsclub/ensemblingneuralnetworks

공식 코드

Towards a Systematic Approach to Design New Ensemble Learning Algorithms

https://github.com/oldaandozerskaya/intimacy_tmn_semeval23_task9

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tmn at SemEval-2023 Task 9: Multilingual Tweet Intimacy Detection using XLM-T, Google Translate, and Ensemble Learning

https://github.com/omidbazgirTTU/IntegratedREFINED

공식 코드

Investigation of REFINED CNN ensemble learning for anti-cancer drug sensitivity prediction

https://github.com/opscidia/bagbert

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BagBERT: BERT-based bagging-stacking for multi-topic classification

https://github.com/pablorom2004/insight-buddy-ai-app

공식 코드

INSIGHTBUDDY-AI: Medication Extraction and Entity Linking using Large Language Models and Ensemble Learning

https://github.com/plbenveniste/lungcancerrisk

공식 코드

Development and external validation of a lung cancer risk estimation tool using gradient-boosting

https://github.com/pokaxpoka/sunrise

공식 코드

SUNRISE: A Simple Unified Framework for Ensemble Learning in Deep Reinforcement Learning

https://github.com/polsean/xtdml

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Double Machine Learning for Static Panel Models with Fixed Effects

https://github.com/poyuhs/model-free-robotics

공식 코드

Comparative Evaluation of Learning Models for Bionic Robots: Non-Linear Transfer Function Identifications

https://github.com/pycroscopy/atomai

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AtomAI: A Deep Learning Framework for Analysis of Image and Spectroscopy Data in (Scanning) Transmission Electron Microscopy and Beyond

https://github.com/pzivich/publications-code/tree/master/DoubleCrossFit

공식 코드

Machine learning for causal inference: on the use of cross-fit estimators

https://github.com/qiaoyu-tan/E2GNN

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E2GNN: Efficient Graph Neural Network Ensembles for Semi-Supervised Classification

https://github.com/qingquan63/fairemol

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Mitigating Unfairness via Evolutionary Multi-objective Ensemble Learning

https://github.com/raduionescu/MOROCO-Tweets

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The Unreasonable Effectiveness of Machine Learning in Moldavian versus Romanian Dialect Identification

https://github.com/rafael-a-monteiro-math/Binary_classification_phase_separation

공식 코드

Binary Classification as a Phase Separation Process

https://github.com/rifqat/Comparative-Analysis

공식 코드

A Comparative Analysis of the Ensemble Methods for Drug Design

https://github.com/rizaozcelik/pydebiaseddta

공식 코드

DebiasedDTA: A Framework for Improving the Generalizability of Drug-Target Affinity Prediction Models

https://github.com/rizavelioglu/hateful_memes-hate_detectron

공식 코드

Detecting Hate Speech in Memes Using Multimodal Deep Learning Approaches: Prize-winning solution to Hateful Memes Challenge

https://github.com/rsamf/text-guided-mixup

공식 코드

Text-Guided Mixup Towards Long-Tailed Image Categorization

https://github.com/rub-ksv/semeval-task5-mami

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RubCSG at SemEval-2022 Task 5: Ensemble learning for identifying misogynous MEMEs

https://github.com/rucaibox/competitive-icl

공식 코드

Investigating the Pre-Training Dynamics of In-Context Learning: Task Recognition vs. Task Learning

https://github.com/salmon1802/ektf

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Ensemble Learning via Knowledge Transfer for CTR Prediction

https://github.com/sarfrazahmad307/ibitter-stack

공식 코드

iBitter-Stack: A Multi-Representation Ensemble Learning Model for Accurate Bitter Peptide Identification

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

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

https://github.com/sepehrbakhshi/BELS

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A Broad Ensemble Learning System for Drifting Stream Classification

https://github.com/sepehrbakhshi/ml-bels

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Balancing Efficiency vs. Effectiveness and Providing Missing Label Robustness in Multi-Label Stream Classification

https://github.com/sh4174/hypernetensemble

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Hypernet-Ensemble Learning of Segmentation Probability for Medical Image Segmentation with Ambiguous Labels

https://github.com/shaoeric/Decoupled-Knowledge-with-Ensemble-Learning-for-Online-Distillation

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Decoupled Knowledge with Ensemble Learning for Online Distillation

https://github.com/shiralab/opendg-eval

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Simple Domain Generalization Methods are Strong Baselines for Open Domain Generalization

https://github.com/shrezaei/MI-on-EL

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Accuracy-Privacy Trade-off in Deep Ensemble: A Membership Inference Perspective

https://github.com/shuningjin/SemEval2018-Task2-EmojiDetection

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Duluth UROP at SemEval-2018 Task 2: Multilingual Emoji Prediction with Ensemble Learning and Oversampling

https://github.com/sm3a96/ids-machine-learning-techniques-

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A Comprehensive Comparative Study of Individual ML Models and Ensemble Strategies for Network Intrusion Detection Systems

https://github.com/smallcube/EAL-GAN

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

https://github.com/smlab-niser/Google-Reviews-Sentiment-Analysis

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Comparative Sentiment Analysis of App Reviews

https://github.com/statmlben/ensLoss

공식 코드

EnsLoss: Stochastic Calibrated Loss Ensembles for Preventing Overfitting in Classification

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