https://github.com/yanllan-ljb/contrastivegaussian
공식 코드ContrastiveGaussian: High-Fidelity 3D Generation with Contrastive Learning and Gaussian Splatting
Papers with Code 아카이브
Contrastive Learning
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Contrastive Learning is a deep learning technique for unsupervised representation learning. The goal is to learn a representation of data such that similar instances are close together in the representation space, while dissimilar instances are far apart.
It has been shown to be effective in various computer vision and natural language processing tasks, including image retrieval, zero-shot learning, and cross-modal retrieval. In these tasks, the learned representations can be used as features for downstream tasks such as classification and clustering.
<span style="color:grey; opacity: 0.6">(Image credit: Schroff et al. 2015)</span>
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/yanndubs/invariant-self-supervised-learning
공식 코드Improving Self-Supervised Learning by Characterizing Idealized Representations
https://github.com/yanran-tang/casegnn
공식 코드CaseGNN++: Graph Contrastive Learning for Legal Case Retrieval with Graph Augmentation
https://github.com/yanzhen4/logicol
공식 코드LogiCoL: Logically-Informed Contrastive Learning for Set-based Dense Retrieval
https://github.com/yaohungt/Barlow-Twins-HSIC
공식 코드A Note on Connecting Barlow Twins with Negative-Sample-Free Contrastive Learning
https://github.com/yaolinli/idc
공식 코드Image Difference Captioning with Pre-training and Contrastive Learning
https://github.com/yashkant/concat-vqa
공식 코드https://github.com/yassouali/SCL
공식 코드https://github.com/yaushian/msimcse
공식 코드English Contrastive Learning Can Learn Universal Cross-lingual Sentence Embeddings
https://github.com/yawencui/cmoa
공식 코드Generalized Few-Shot Continual Learning with Contrastive Mixture of Adapters
https://github.com/ybdai7/Chameleon-durable-backdoor
공식 코드Chameleon: Adapting to Peer Images for Planting Durable Backdoors in Federated Learning
https://github.com/ybio/lag
공식 코드https://github.com/ycaigogogo/cvpr24-coder
공식 코드Leveraging Cross-Modal Neighbor Representation for Improved CLIP Classification
https://github.com/ychang686/scs-co
공식 코드SCS-Co: Self-Consistent Style Contrastive Learning for Image Harmonization
https://github.com/ychen1993/coserec
공식 코드Contrastive Self-supervised Sequential Recommendation with Robust Augmentation
https://github.com/ycheoo/fppl
공식 코드FPPL: An Efficient and Non-IID Robust Federated Continual Learning Framework
https://github.com/ydongd/prototypical-prompt-verbalizer
공식 코드Eliciting Knowledge from Pretrained Language Models for Prototypical Prompt Verbalizer
https://github.com/yeonjun-in/torch-sp-agcl
공식 코드Similarity Preserving Adversarial Graph Contrastive Learning
https://github.com/yeonsw/rankencoder
공식 코드Ranking-Enhanced Unsupervised Sentence Representation Learning
https://github.com/yeungchenwa/fontdiffuser
공식 코드https://github.com/yflyl613/AdaptSSR
공식 코드AdaptSSR: Pre-training User Model with Augmentation-Adaptive Self-Supervised Ranking
https://github.com/yflyl613/fedrec
공식 코드https://github.com/yflyzhang/rankpo
공식 코드https://github.com/ygjwd12345/UCD
공식 코드Uncertainty-aware Contrastive Distillation for Incremental Semantic Segmentation
https://github.com/yh-han/gsc
공식 코드Generative Subgraph Contrast for Self-Supervised Graph Representation Learning
https://github.com/yh0517/afloc
공식 코드https://github.com/yibai-shi/dwgf
공식 코드A Diffusion Weighted Graph Framework for New Intent Discovery
https://github.com/yibin-lei/recontriever
공식 코드Unsupervised Dense Retrieval with Relevance-Aware Contrastive Pre-Training
https://github.com/yichaocai1/crossmodal_mislaignment
공식 코드On the Value of Cross-Modal Misalignment in Multimodal Representation Learning
https://github.com/yichenzw/coh-mgt-detection
공식 코드https://github.com/yifan-song793/eto
공식 코드Trial and Error: Exploration-Based Trajectory Optimization for LLM Agents
https://github.com/yifan-song793/infocl
공식 코드https://github.com/yifang-qin/disenpoi
공식 코드DisenPOI: Disentangling Sequential and Geographical Influence for Point-of-Interest Recommendation
https://github.com/yifanzhang-pro/kernel-infonce
공식 코드Contrastive Learning Is Spectral Clustering On Similarity Graph
https://github.com/yifanzhang-pro/m-mae
공식 코드https://github.com/yifanzhang-pro/matrix-llm
공식 코드출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.