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Diversity
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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/wjx-git/Review-Instruct
공식 코드https://github.com/wkim97/ada
공식 코드Diverse Generative Perturbations on Attention Space for Transferable Adversarial Attacks
https://github.com/wofmanaf/ResT
공식 코드https://github.com/woldier/siamseg
공식 코드https://github.com/woshisad159/tfnet
공식 코드A Chinese Continuous Sign Language Dataset Based on Complex Environments
https://github.com/wpoelman/typ-div
공식 코드https://github.com/wpoelman/typ-div-survey
공식 코드https://github.com/wpp13749/block_flow
공식 코드https://github.com/wq13552463699/clustering-for-offline-rl-il
공식 코드https://github.com/wtjiang98/PoseTrans
공식 코드PoseTrans: A Simple Yet Effective Pose Transformation Augmentation for Human Pose Estimation
https://github.com/wutad-wjy/charms
공식 코드CHARMS: A Cognitive Hierarchical Agent for Reasoning and Motion Stylization in Autonomous Driving
https://github.com/wutaiqiang/llm_kd_akl
공식 코드Rethinking Kullback-Leibler Divergence in Knowledge Distillation for Large Language Models
https://github.com/wuuu110/SpadePSO
공식 코드Incorporating Surprisingly Popular Algorithm and Euclidean Distance-based Adaptive Topology into PSO
https://github.com/wuxiaofei01/fastgrasp
공식 코드https://github.com/wuyxin/graphmetro
공식 코드GraphMETRO: Mitigating Complex Graph Distribution Shifts via Mixture of Aligned Experts
https://github.com/wuzengqing001225/consensusdiversitytradeoffmas
공식 코드https://github.com/wwweiwei/track2vec
공식 코드Track2Vec: fairness music recommendation with a GPU-free customizable-driven framework
https://github.com/wxljz/laida
공식 코드https://github.com/wyf-accept/backtoreality
공식 코드Back to Reality: Weakly-supervised 3D Object Detection with Shape-guided Label Enhancement
https://github.com/wyky481l/mmcd
공식 코드A Multi-Modal Contrastive Diffusion Model for Therapeutic Peptide Generation
https://github.com/wyu-du/gp-vae
공식 코드Diverse Text Generation via Variational Encoder-Decoder Models with Gaussian Process Priors
https://github.com/wyu97/permgen
공식 코드https://github.com/wzm5853/bench4merge
공식 코드https://github.com/wznpub/MMA_Regularization
공식 코드MMA Regularization: Decorrelating Weights of Neural Networks by Maximizing the Minimal Angles
https://github.com/xduxyli/scen-master
공식 코드Siamese Contrastive Embedding Network for Compositional Zero-Shot Learning
https://github.com/xdxie/WAS_WordArt-Segmentation
공식 코드https://github.com/xhan77/ssd-lm
공식 코드https://github.com/xiangchenchao/ddpn
공식 코드Rethinking Diversified and Discriminative Proposal Generation for Visual Grounding
https://github.com/xiaofei-cn/incremental-evolution-pose-generation
공식 코드Direct May Not Be the Best: An Incremental Evolution View of Pose Generation
https://github.com/xiaohua-chen/risda
공식 코드https://github.com/xiaoiker/meta_dpm
공식 코드Metadata-Conditioned Generative Models to Synthesize Anatomically-Plausible 3D Brain MRIs
https://github.com/xiaojieli0903/genview
공식 코드GenView: Enhancing View Quality with Pretrained Generative Model for Self-Supervised Learning
https://github.com/xiaolongo/MaxMIAcrossFT
공식 코드Maximizing Mutual Information Across Feature and Topology Views for Learning Graph Representations
https://github.com/xiaomenglilili/dh-mamba
공식 코드DH-Mamba: Exploring Dual-domain Hierarchical State Space Models for MRI Reconstruction
https://github.com/xiaomenglilili/dm-mamba
공식 코드DH-Mamba: Exploring Dual-domain Hierarchical State Space Models for MRI Reconstruction
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.