SOTAVerified

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

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Showing 2101–2125 of 10307 papers

TitleStatusHype
Transfer Learning of Surrogate Models via Domain Affine Transformation Across Synthetic and Real-World Benchmarks—0
Bridging The Multi-Modality Gaps of Audio, Visual and Linguistic for Speech Enhancement—0
On the Transfer of Knowledge in Quantum Algorithms—0
Contrastive Representation Learning Helps Cross-institutional Knowledge Transfer: A Study in Pediatric Ventilation Management—0
Skin Disease Detection and Classification of Actinic Keratosis and Psoriasis Utilizing Deep Transfer Learning—0
GenTL: A General Transfer Learning Model for Building Thermal DynamicsCode0
2-Tier SimCSE: Elevating BERT for Robust Sentence Embeddings—0
LLM4WM: Adapting LLM for Wireless Multi-Tasking—0
Multimodal AI on Wound Images and Clinical Notes for Home Patient Referral—0
EchoLM: Accelerating LLM Serving with Real-time Knowledge Distillation—0
Heterogeneous Federated Learning Systems for Time-Series Power Consumption Prediction with Multi-Head Embedding Mechanism—0
Heterogeneous Federated Learning System for Sparse Healthcare Time-Series Prediction—0
A novel Trunk Branch-net PINN for flow and heat transfer prediction in porous medium—0
Bidirectional Brain Image Translation using Transfer Learning from Generic Pre-trained Models—0
Efficient PINNs: Multi-Head Unimodular Regularization of the Solutions Space—0
On the Adversarial Vulnerabilities of Transfer Learning in Remote Sensing—0
Energy Consumption Reduction for UAV Trajectory Training : A Transfer Learning Approach—0
Rethinking Membership Inference Attacks Against Transfer Learning—0
Enhancing Brain Tumor Segmentation Using Channel Attention and Transfer learningCode0
BeST -- A Novel Source Selection Metric for Transfer Learning—0
Adaptive Target Localization under Uncertainty using Multi-Agent Deep Reinforcement Learning with Knowledge Transfer—0
Transfer Learning Strategies for Pathological Foundation Models: A Systematic Evaluation in Brain Tumor Classification—0
A Resource-Efficient Training Framework for Remote Sensing Text--Image RetrievalCode0
Model-Robust and Adaptive-Optimal Transfer Learning for Tackling Concept Shifts in Nonparametric Regression—0
Automatic Speech Recognition for Sanskrit with Transfer Learning—0
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All datasetsOffice-Home100 sleep nights of 8 caregiversBanglaLekha Isolated DatasetCOCO70KITTI Object Tracking Evaluation 2012Retinal Fundus MultiDisease Image Dataset (RFMiD)

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1APCLIPAccuracy84.2—Unverified
2DFA-ENTAccuracy69.2—Unverified
3DFA-SAFNAccuracy69.1—Unverified
4EasyTLAccuracy63.3—Unverified
5MEDAAccuracy60.3—Unverified
#ModelMetricClaimedVerifiedStatus
1CNN10-20% Mask PSNR3.23—Unverified
#ModelMetricClaimedVerifiedStatus
1Chatterjee, Dutta et al.[1]Accuracy96.12—Unverified
#ModelMetricClaimedVerifiedStatus
1Co-TuningAccuracy85.65—Unverified
#ModelMetricClaimedVerifiedStatus
1Physical AccessEER5.74—Unverified
#ModelMetricClaimedVerifiedStatus
1riadd.aucmediAUROC0.95—Unverified