Transfer Learning

Transfer Learning is a machine learning technique where a model trained on one task is re-purposed and fine-tuned for a related, but different task. The idea behind transfer learning is to leverage the knowledge learned from a pre-trained model to solve a new, but related problem. This can be useful in situations where there is limited data available to train a new model from scratch, or when the new task is similar enough to the original task that the pre-trained model can be adapted to the new problem with only minor modifications.

( Image credit: Subodh Malgonde )

Papers

Recently Added Most Hyped Most Active Needs Verification Most Verified

Showing 2611–2620 of 10307 papers

Title	Date	Tasks	Status	Hype
De-novo Chemical Reaction Generation by Means of Temporal Convolutional Neural Networks	Oct 26, 2023	Language ModellingTransfer Learning	—Unverified	0
PETA: Evaluating the Impact of Protein Transfer Learning with Sub-word Tokenization on Downstream Applications	Oct 26, 2023	Language ModelingLanguage Modelling	CodeCode Available	1
Fantastic Gains and Where to Find Them: On the Existence and Prospect of General Knowledge Transfer between Any Pretrained Model	Oct 26, 2023	Data AugmentationGeneral Knowledge	CodeCode Available	0
Deep Learning on SAR Imagery: Transfer Learning Versus Randomly Initialized Weights	Oct 26, 2023	Deep LearningTransfer Learning	CodeCode Available	1
Transfer of Reinforcement Learning-Based Controllers from Model- to Hardware-in-the-Loop	Oct 25, 2023	Reinforcement Learning (RL)Transfer Learning	—Unverified	0
Learning Transfers over Several Programming Languages	Oct 25, 2023	Cross-Lingual TransferIn-Context Learning	—Unverified	0
An Efficient Deep Learning-based approach for Recognizing Agricultural Pests in the Wild	Oct 25, 2023	Transfer Learning	—Unverified	0
Transferring a molecular foundation model for polymer property predictions	Oct 25, 2023	Data AugmentationTransfer Learning	—Unverified	0
CommonCanvas: An Open Diffusion Model Trained with Creative-Commons Images	Oct 25, 2023	Transfer Learning	CodeCode Available	2
Deep machine learning for meteor monitoring: advances with transfer learning and gradient-weighted class activation mapping	Oct 25, 2023	Transfer Learning	—Unverified	0

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All datasets Office-Home 100 sleep nights of 8 caregivers BanglaLekha Isolated Dataset COCO70 KITTI Object Tracking Evaluation 2012 Retinal Fundus MultiDisease Image Dataset (RFMiD)

Benchmark Results

#	Model	Metric	Claimed	Verified	Status
1	APCLIP	Accuracy	84.2	—	Unverified
2	DFA-ENT	Accuracy	69.2	—	Unverified
3	DFA-SAFN	Accuracy	69.1	—	Unverified
4	EasyTL	Accuracy	63.3	—	Unverified
5	MEDA	Accuracy	60.3	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	CNN	10-20% Mask PSNR	3.23	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Chatterjee, Dutta et al.[1]	Accuracy	96.12	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Co-Tuning	Accuracy	85.65	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Physical Access	EER	5.74	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	riadd.aucmedi	AUROC	0.95	—	Unverified