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 151–175 of 10307 papers

Title	Date	Tasks	Status	Hype
CLIP-Driven Universal Model for Organ Segmentation and Tumor Detection	Jan 2, 2023	Organ SegmentationSegmentation	CodeCode Available	2
CommonCanvas: An Open Diffusion Model Trained with Creative-Commons Images	Oct 25, 2023	Transfer Learning	CodeCode Available	2
Feature Learning in Infinite-Width Neural Networks	Nov 30, 2020	Few-Shot LearningTransfer Learning	CodeCode Available	2
BiomedGPT: A Generalist Vision-Language Foundation Model for Diverse Biomedical Tasks	May 26, 2023	Image CaptioningMedical Visual Question Answering	CodeCode Available	2
All-in-one foundational models learning across quantum chemical levels	Sep 18, 2024	AllCloud Computing	CodeCode Available	2
FlashST: A Simple and Universal Prompt-Tuning Framework for Traffic Prediction	May 28, 2024	In-Context LearningPrediction	CodeCode Available	2
3D UX-Net: A Large Kernel Volumetric ConvNet Modernizing Hierarchical Transformer for Medical Image Segmentation	Sep 29, 2022	Image SegmentationMedical Image Segmentation	CodeCode Available	2
Quantformer: from attention to profit with a quantitative transformer trading strategy	Mar 30, 2024	Sentiment AnalysisTransfer Learning	CodeCode Available	2
Actuarial Applications of Natural Language Processing Using Transformers: Case Studies for Using Text Features in an Actuarial Context	Jun 4, 2022	Transfer Learning	CodeCode Available	2
CARTE: Pretraining and Transfer for Tabular Learning	Feb 26, 2024	Data IntegrationTransfer Learning	CodeCode Available	2
AXIAL: Attention-based eXplainability for Interpretable Alzheimer's Localized Diagnosis using 2D CNNs on 3D MRI brain scans	Jul 2, 2024	3D ClassificationAlzheimer's Disease Detection	CodeCode Available	2
K-LITE: Learning Transferable Visual Models with External Knowledge	Apr 20, 2022	BenchmarkingDescriptive	CodeCode Available	2
CascadeTabNet: An approach for end to end table detection and structure recognition from image-based documents	Apr 27, 2020	Image AugmentationTable Detection	CodeCode Available	2
Leveraging medical Twitter to build a visual–language foundation model for pathology AI	Apr 1, 2023	Transfer Learning	CodeCode Available	2
Constructing and Exploring Intermediate Domains in Mixed Domain Semi-supervised Medical Image Segmentation	Apr 13, 2024	Domain AdaptationImage Segmentation	CodeCode Available	2
LightGaussian: Unbounded 3D Gaussian Compression with 15x Reduction and 200+ FPS	Nov 28, 2023	Knowledge DistillationNeRF	CodeCode Available	2
Discovery of 2D materials using Transformer Network based Generative Design	Jan 14, 2023	Formation EnergySelf-Learning	CodeCode Available	2
LP-MusicCaps: LLM-Based Pseudo Music Captioning	Jul 31, 2023	Language ModelingLanguage Modelling	CodeCode Available	2
An Upload-Efficient Scheme for Transferring Knowledge From a Server-Side Pre-trained Generator to Clients in Heterogeneous Federated Learning	Mar 23, 2024	Federated LearningTransfer Learning	CodeCode Available	2
How Well Do Sparse Imagenet Models Transfer?	Nov 26, 2021	Transfer Learning	CodeCode Available	2
AutoKE: An automatic knowledge embedding framework for scientific machine learning	May 11, 2022	BIG-bench Machine LearningNeural Architecture Search	CodeCode Available	1
AutoInit: Analytic Signal-Preserving Weight Initialization for Neural Networks	Sep 18, 2021	Meta-LearningNeural Architecture Search	CodeCode Available	1
Automated Cloud Provisioning on AWS using Deep Reinforcement Learning	Sep 13, 2017	Cloud ComputingDeep Reinforcement Learning	CodeCode Available	1
Authorship Style Transfer with Policy Optimization	Mar 12, 2024	Style TransferTransfer Learning	CodeCode Available	1
A unified scalable framework for causal sweeping strategies for Physics-Informed Neural Networks (PINNs) and their temporal decompositions	Feb 28, 2023	Transfer Learning	CodeCode Available	1

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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