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Multi-Label Classification

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Multi-Label Classification is the supervised learning problem where an instance may be associated with multiple labels. This is an extension of single-label classification (i.e., multi-class, or binary) where each instance is only associated with a single class label.

Source: Deep Learning for Multi-label Classification

코드

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

https://github.com/nilesh2797/dexml

공식 코드

Dual-Encoders for Extreme Multi-Label Classification

https://github.com/nilesh2797/elias

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ELIAS: End-to-End Learning to Index and Search in Large Output Spaces

https://github.com/ning-mz/sca-gps

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A Symbolic Character-Aware Model for Solving Geometry Problems

https://github.com/nisarahmedrana/arabicmlec

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Improving Arabic Multi-Label Emotion Classification using Stacked Embeddings and Hybrid Loss Function

https://github.com/nkatzz/OLED

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Semi-Supervised Online Structure Learning for Composite Event Recognition

https://github.com/nlpAThits/hyfi

공식 코드

A Fully Hyperbolic Neural Model for Hierarchical Multi-Class Classification

https://github.com/onlyzdd/ecg-diagnosis

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Interpretable Deep Learning for Automatic Diagnosis of 12-lead Electrocardiogram

https://github.com/open-compass/lawbench

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LawBench: Benchmarking Legal Knowledge of Large Language Models

https://github.com/opendatalab/h2rsvlm

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VHM: Versatile and Honest Vision Language Model for Remote Sensing Image Analysis

https://github.com/opendatalab/vhm

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VHM: Versatile and Honest Vision Language Model for Remote Sensing Image Analysis

https://github.com/openseg-group/mlseg

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RankSeg: Adaptive Pixel Classification with Image Category Ranking for Segmentation

https://github.com/openseg-group/rankseg

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RankSeg: Adaptive Pixel Classification with Image Category Ranking for Segmentation

https://github.com/openvinotoolkit/deep-object-reid

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Combining Metric Learning and Attention Heads For Accurate and Efficient Multilabel Image Classification

https://github.com/oracle/tribuo

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Tribuo: Machine Learning with Provenance in Java

https://github.com/orion-ai-lab/eouncertaintygeneralization

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On the Generalization of Representation Uncertainty in Earth Observation

https://github.com/ptirupat/MLAD

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Modeling Multi-Label Action Dependencies for Temporal Action Localization

https://github.com/ptrajdos/rrcBasedClassifiers

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Bayes metaclassifier and Soft-confusion-matrix classifier in the task of multi-label classification

https://github.com/pulkitparikh/sexism_classification

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Multi-label Categorization of Accounts of Sexism using a Neural Framework

https://github.com/pxaris/lc-protonets

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LC-Protonets: Multi-Label Few-Shot Learning for World Music Audio Tagging

https://github.com/quwenjie/multiguard

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MultiGuard: Provably Robust Multi-label Classification against Adversarial Examples

https://github.com/rajcscw/nlp-gym

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NLPGym -- A toolkit for evaluating RL agents on Natural Language Processing Tasks

https://github.com/rhyssiyan/online.inc.seg-pytorch

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An EM Framework for Online Incremental Learning of Semantic Segmentation

https://github.com/risojevicv/rssc-transfer

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Do we still need ImageNet pre-training in remote sensing scene classification?

https://github.com/rohban-lab/swinchex

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SwinCheX: Multi-label classification on chest X-ray images with transformers

https://github.com/rooooyy/hill

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HILL: Hierarchy-aware Information Lossless Contrastive Learning for Hierarchical Text Classification

https://github.com/rooooyy/hitin

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HiTIN: Hierarchy-aware Tree Isomorphism Network for Hierarchical Text Classification

https://github.com/rwightman/pytorch-image-models

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TResNet: High Performance GPU-Dedicated Architecture

https://github.com/sadimanna/skid

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SKID: Self-Supervised Learning for Knee Injury Diagnosis from MRI Data

https://github.com/sadimanna/sslm

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SKID: Self-Supervised Learning for Knee Injury Diagnosis from MRI Data

https://github.com/sarthak268/sample-efficient-visual-concept-learning

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Sample-Efficient Learning of Novel Visual Concepts

https://github.com/satyadevntv/ROT

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Efficient Robust Optimal Transport with Application to Multi-Label Classification

https://github.com/schariya/infwalk

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InfiniteWalk: Deep Network Embeddings as Laplacian Embeddings with a Nonlinearity

https://github.com/sciencenlp-lab/llm-ssc

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Multi-label Sequential Sentence Classification via Large Language Model

https://github.com/scikit-multilearn/scikit-multilearn

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A scikit-based Python environment for performing multi-label classification

https://github.com/sebischair/fusionsent

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Efficient Few-shot Learning for Multi-label Classification of Scientific Documents with Many Classes

https://github.com/seilna/youtube-8m

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Encoding Video and Label Priors for Multi-label Video Classification on YouTube-8M dataset

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