Papers with Code 아카이브
Diversity
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
- 하위 태스크
- 0
- 평가표
- 0
- 보존된 평가 기록
- 0
Diversity in data sampling is crucial across various use cases, including search, recommendation systems, and more. Ensuring diverse samples means capturing a wide range of variations and perspectives, which leads to more robust, unbiased, and comprehensive models. In search use cases, for instance, diversity helps avoid redundancy, ensuring that users are exposed to a broader set of relevant information rather than repeated similar results.
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/MarisaKirisame/unroll_gan
https://github.com/MartinPawel/ProbabilisticallyRobustRecourse
Explaining Machine Learning Classifiers through Diverse Counterfactual Explanations
https://github.com/Mckinsey666/ACGAN-Anime-Generation
https://github.com/Mckinsey666/Anime-Generation
https://github.com/MeetXinZhang/EEG-ConvTransformer
EEG-ConvTransformer for Single-Trial EEG based Visual Stimuli Classification
https://github.com/Merenguelkl/Reverse_Disstilation
Anomaly Detection via Reverse Distillation from One-Class Embedding
https://github.com/MiaoyunZhao/GANTransferLimitedData
Image Generation From Small Datasets via Batch Statistics Adaptation
https://github.com/Michedev/DDPM-Pytorch
https://github.com/Mind23-2/MindCode-101/tree/main/lenet
Hyperparameter Ensembles for Robustness and Uncertainty Quantification
https://github.com/Mind23-2/MindCode-4/tree/main/gat
DGCN: Diversified Recommendation with Graph Convolutional Networks
https://github.com/MindCode-4/code-10/tree/main/UColor
Underwater Image Enhancement via Medium Transmission-Guided Multi-Color Space Embedding
https://github.com/MindCode-4/code-11/tree/main/factorized-attention
https://github.com/MindCode-4/code-12/tree/main/multimodal-trajectory
https://github.com/MindCode-4/code-14/tree/main/AVA_cifar
AAG: Self-Supervised Representation Learning by Auxiliary Augmentation with GNT-Xent Loss
https://github.com/MindCode-4/code-14/tree/main/UColor
Underwater Image Enhancement via Medium Transmission-Guided Multi-Color Space Embedding
https://github.com/MindCode-4/code-2/tree/main/pix2struct
Pix2Struct: Screenshot Parsing as Pretraining for Visual Language Understanding
https://github.com/MindSpore-MS-Code2/code0/tree/main/ecolite
https://github.com/MindSpore-paper-code-3/code1/tree/main/AVA_cifar
AAG: Self-Supervised Representation Learning by Auxiliary Augmentation with GNT-Xent Loss
https://github.com/MindSpore-paper-code-3/code10/tree/main/guided_anchoring
https://github.com/MindSpore-paper-code-3/code2/tree/main/DDM
Progressive Attention on Multi-Level Dense Difference Maps for Generic Event Boundary Detection
https://github.com/MindSpore-scientific-2/code-10/tree/main/SVGD
SVGDreamer++: Advancing Editability and Diversity in Text-Guided SVG Generation
https://github.com/MindSpore-scientific-2/code-14/tree/main/m2m_100
M2m: Imbalanced Classification via Major-to-minor Translation
https://github.com/MindSpore-scientific/code-13/tree/main/SVGD
https://github.com/MindSpore-scientific/code-3/tree/main/auxiliary-tasks-in-multi-task-learning
https://github.com/MindSpore-scientific/code-8/tree/main/QuantExplainNLP_AlgoAnalysis
https://github.com/Mistral-Twirl/3D-Point-Cloud-Metrics
Learning Representations and Generative Models for 3D Point Clouds
https://github.com/MoSubaiei/modified-SINDy
https://github.com/MustafaAshraf348/Skin-Disease-Analyzer
https://github.com/NIRVANALAN/magnifiernet_reid
MagnifierNet: Towards Semantic Adversary and Fusion for Person Re-identification
https://github.com/NIRVANALAN/reid_baseline
https://github.com/Namkyeong/NoisyNodes_Pytorch
Simple GNN Regularisation for 3D Molecular Property Prediction & Beyond
https://github.com/Neeleshrj/Image-Colorization-API
https://github.com/NikhilBadami/YogiAI
Yoga-82: A New Dataset for Fine-grained Classification of Human Poses
https://github.com/Nimesh-Patel/text-to-text-transfer-transformer
Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer
https://github.com/NisansaDdS/Some-Languages-are-More-Equal-than-Others
The State and Fate of Linguistic Diversity and Inclusion in the NLP World
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.