Contrastive Learning

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.

(Image credit: Schroff et al. 2015)

Papers

Recently Added Most Hyped Most Active Needs Verification Most Verified

Showing 3151–3160 of 6661 papers

Title	Date	Tasks	Status
Your Graph Recommender is Provably a Single-view Graph Contrastive Learning	Jul 25, 2024	Contrastive LearningGraph Neural Network	—Unverified
X-Sample Contrastive Loss: Improving Contrastive Learning with Sample Similarity Graphs	Jul 25, 2024	Contrastive Learning	—Unverified
Speed-enhanced Subdomain Adaptation Regression for Long-term Stable Neural Decoding in Brain-computer Interfaces	Jul 25, 2024	Contrastive LearningDomain Adaptation	—Unverified
Banyan: Improved Representation Learning with Explicit Structure	Jul 25, 2024	Contrastive LearningRepresentation Learning	—Unverified
SMA-Hyper: Spatiotemporal Multi-View Fusion Hypergraph Learning for Traffic Accident Prediction	Jul 24, 2024	Contrastive LearningGraph Learning	—Unverified
Contrastive Learning Is Not Optimal for Quasiperiodic Time Series	Jul 24, 2024	Contrastive LearningSelf-Supervised Learning	—Unverified
Distribution-Aware Robust Learning from Long-Tailed Data with Noisy Labels	Jul 23, 2024	Contrastive Learning	CodeCode Available
Masks and Manuscripts: Advancing Medical Pre-training with End-to-End Masking and Narrative Structuring	Jul 23, 2024	Contrastive LearningMedical Image Analysis	—Unverified
Tackling Feature-Classifier Mismatch in Federated Learning via Prompt-Driven Feature Transformation	Jul 23, 2024	Contrastive LearningFederated Learning	—Unverified
A Multi-view Mask Contrastive Learning Graph Convolutional Neural Network for Age Estimation	Jul 23, 2024	Age EstimationContrastive Learning	—Unverified

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All datasets imagenet-1k 10,000 People - Human Pose Recognition Data CIFAR-10 STL-10

Benchmark Results

#	Model	Metric	Claimed	Verified	Status
1	ResNet50	ImageNet Top-1 Accuracy	73.6	—	Unverified
2	ResNet50	ImageNet Top-1 Accuracy	73	—	Unverified
3	ResNet50	ImageNet Top-1 Accuracy	71.1	—	Unverified
4	ResNet50	ImageNet Top-1 Accuracy	69.3	—	Unverified
5	ResNet50 (v2)	ImageNet Top-1 Accuracy	67.6	—	Unverified
6	ResNet50 (v2)	ImageNet Top-1 Accuracy	63.8	—	Unverified
7	ResNet50	ImageNet Top-1 Accuracy	63.6	—	Unverified
8	ResNet50	ImageNet Top-1 Accuracy	61.5	—	Unverified
9	ResNet50	ImageNet Top-1 Accuracy	61.5	—	Unverified
10	ResNet50 (4×)	ImageNet Top-1 Accuracy	61.3	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	1	0..5sec	1	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	IPCL (ResNet18)	Accuracy (Top-1)	84.77	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	IPCL (ResNet18)	Accuracy (Top-1)	85.55	—	Unverified