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General Classification

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하위 태스크

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평가표

11

보존된 평가 기록

19

코드

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

https://github.com/PurdueMINDS/size-invariant-GNNs

공식 코드

Size-Invariant Graph Representations for Graph Classification Extrapolations

https://github.com/QData/C-Tran

공식 코드

General Multi-label Image Classification with Transformers

https://github.com/QData/LaMP

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Neural Message Passing for Multi-Label Classification

https://github.com/QData/TextAttack

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BAE: BERT-based Adversarial Examples for Text Classification

https://github.com/QData/TextAttack/blob/master/textattack/attack_recipes/bae_garg_2019.py

공식 코드

BAE: BERT-based Adversarial Examples for Text Classification

https://github.com/QData/deepWordBug

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Black-box Generation of Adversarial Text Sequences to Evade Deep Learning Classifiers

https://github.com/Qidian213/Ranked_Person_ReID

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Ranking and Classification driven Feature Learning for Person Re_identification

https://github.com/Quadflor/quadflor

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Using Titles vs. Full-text as Source for Automated Semantic Document Annotation

https://github.com/Quicksign/ocrized-text-dataset

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Multimodal deep networks for text and image-based document classification

https://github.com/Raibows/RSE-Adversarial-Defense

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Defense of Word-level Adversarial Attacks via Random Substitution Encoding

https://github.com/Randl/kmeans_selfsuper

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Self-Supervised Learning for Large-Scale Unsupervised Image Clustering

https://github.com/RaoulHeese/adasamp-pareto

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Adaptive Sampling of Pareto Frontiers with Binary Constraints Using Regression and Classification

https://github.com/RaptorMai/online-continual-learning

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Online Continual Learning in Image Classification: An Empirical Survey

https://github.com/Raschka-research-group/coral-cnn

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Rank consistent ordinal regression for neural networks with application to age estimation

https://github.com/ReginaMayhem/ClusterBusters

공식 코드

Meta-Learning for One-Class Classification with Few Examples using Order-Equivariant Network

https://github.com/RezaKatebi/Galaxy-Morphology-CapsNet

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Galaxy morphology prediction using capsule networks

https://github.com/RingBDStack/HE-AGCRCNN

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Hierarchical Taxonomy-Aware and Attentional Graph Capsule RCNNs for Large-Scale Multi-Label Text Classification

https://github.com/RingBDStack/HTCInfoMax

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HTCInfoMax: A Global Model for Hierarchical Text Classification via Information Maximization

https://github.com/RockySJ/WDGRL

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Wasserstein Distance Guided Representation Learning for Domain Adaptation

https://github.com/RodentDataAnalytics/mwm-ml-gen

공식 코드

A generalised framework for detailed classification of swimming paths inside the Morris Water Maze

https://github.com/RonsGit/DAEMON-Extraction-Process

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DAEMON: Dataset-Agnostic Explainable Malware Classification Using Multi-Stage Feature Mining

https://github.com/RoyalVane/SEGCN

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Every Node Counts: Self-Ensembling Graph Convolutional Networks for Semi-Supervised Learning

https://github.com/Runjing-Liu120/RaoBlackwellizedSGD

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Rao-Blackwellized Stochastic Gradients for Discrete Distributions

https://github.com/RuoyiDu/PMG-Progressive-Multi-Granularity-Training

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Fine-Grained Visual Classification via Progressive Multi-Granularity Training of Jigsaw Patches

https://github.com/RyanWangZf/Influence_Subsampling

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Less Is Better: Unweighted Data Subsampling via Influence Function

https://github.com/SAP-samples/security-research-dp-hierarchical-text

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On the privacy-utility trade-off in differentially private hierarchical text classification

https://github.com/SGDE2020/embedding_stability

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The Effects of Randomness on the Stability of Node Embeddings

https://github.com/SITE5039/AgrLearn

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Aggregated Learning: A Vector-Quantization Approach to Learning Neural Network Classifiers

https://github.com/SJTU-Thinklab-Det/OHDet_Tensorflow

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On the Arbitrary-Oriented Object Detection: Classification based Approaches Revisited

https://github.com/SLAD-ml/few-shot-ood

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Out-of-Domain Detection for Low-Resource Text Classification Tasks

https://github.com/SMehrkanoon/Deep-brain-state-classification-of-MEG-data

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Deep brain state classification of MEG data

https://github.com/SPINlab/geometry-learning

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Deep Learning for Classification Tasks on Geospatial Vector Polygons

https://github.com/SPOClab-ca/BENDR

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BENDR: using transformers and a contrastive self-supervised learning task to learn from massive amounts of EEG data

https://github.com/Sachin19/adversarial-classify

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Topics to Avoid: Demoting Latent Confounds in Text Classification

https://github.com/Sadegh28/SIFS

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Supervised Infinite Feature Selection

https://github.com/SaeedSharifiMa/AIF

공식 코드

Average Individual Fairness: Algorithms, Generalization and Experiments

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