https://github.com/rezashkv/diffusion_pruning
공식 코드Not All Prompts Are Made Equal: Prompt-based Pruning of Text-to-Image Diffusion Models
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/rgopikrishna-vt/caad
공식 코드Detecting Irregular Network Activity with Adversarial Learning and Expert Feedback
https://github.com/rhermary/plume
공식 코드Removing Geometric Bias in One-Class Anomaly Detection with Adaptive Feature Perturbation
https://github.com/rian-dolphin/stock-embeddings
공식 코드Contrastive Learning of Asset Embeddings from Financial Time Series
https://github.com/rickltt/punctuation_restoration
공식 코드A Small and Fast BERT for Chinese Medical Punctuation Restoration
https://github.com/riemanngraph/motifrgc
공식 코드Motif-aware Riemannian Graph Neural Network with Generative-Contrastive Learning
https://github.com/rikoli/wacv23-workshop-tmgf
공식 코드Transformer Based Multi-Grained Features for Unsupervised Person Re-Identification
https://github.com/ringbdstack/icl-incremental-infonce
공식 코드Unbiased and Efficient Self-Supervised Incremental Contrastive Learning
https://github.com/ringbdstack/ucl_sed
공식 코드Uncertainty-guided Boundary Learning for Imbalanced Social Event Detection
https://github.com/rinnesz/clga
공식 코드Unsupervised Graph Poisoning Attack via Contrastive Loss Back-propagation
https://github.com/risabbiswas/knowledge-distillation-in-medical-image-segmentation
공식 코드Multi-Task Multi-Scale Contrastive Knowledge Distillation for Efficient Medical Image Segmentation
https://github.com/rishabbala/contrastive_learning_for_object_detection
공식 코드https://github.com/rjiang03/Hard-Negative-Sampling-via-Regularized-Optimal-Transport-for-Contrastive-Representation-Learning
공식 코드Hard Negative Sampling via Regularized Optimal Transport for Contrastive Representation Learning
https://github.com/rjiang03/h-scl
공식 코드https://github.com/rjiang03/hcl
공식 코드https://github.com/rjiang03/hcl-ot
공식 코드Hard Negative Sampling via Regularized Optimal Transport for Contrastive Representation Learning
https://github.com/rkmtlab/LipLearner
공식 코드LipLearner: Customizable Silent Speech Interactions on Mobile Devices
https://github.com/robin-karlsson0/vice
공식 코드https://github.com/rogerferrod/crodino-kd
공식 코드https://github.com/rogerferrod/rsicrc
공식 코드Towards a multimodal framework for remote sensing image change retrieval and captioning
https://github.com/rohanshad/cmr_transformer
공식 코드https://github.com/rohit-kundu/ideal-icassp23
공식 코드IDEAL: Improved DEnse locAL Contrastive Learning for Semi-Supervised Medical Image Segmentation
https://github.com/rooooyy/hill
공식 코드HILL: Hierarchy-aware Information Lossless Contrastive Learning for Hierarchical Text Classification
https://github.com/rooshy-yang/becl
공식 코드Behavior Contrastive Learning for Unsupervised Skill Discovery
https://github.com/root0yang/blindnet
공식 코드https://github.com/rosewang2008/language_modeling_via_stochastic_processes
공식 코드https://github.com/rosieyuu/wch
공식 코드https://github.com/roxie62/embed-and-emulate
공식 코드https://github.com/roxie62/neural_operators_for_chaos
공식 코드Training neural operators to preserve invariant measures of chaotic attractors
https://github.com/roychowdhuryresearch/odmo
공식 코드https://github.com/roydenwa/cell-centroid-former
공식 코드https://github.com/roydenwa/pseudo-colorize-masked-cells
공식 코드https://github.com/royny/self-eval
공식 코드https://github.com/rpl-cmu/bevloc
공식 코드BEVLoc: Cross-View Localization and Matching via Birds-Eye-View Synthesis
https://github.com/rsalganik1123/larp
공식 코드LARP: Language Audio Relational Pre-training for Cold-Start Playlist Continuation
https://github.com/rshaojimmy/multimodal-deepfake
공식 코드출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.