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

Showing 21762200 of 10307 papers

TitleStatusHype
Generating Thermal Human Faces for Physiological Assessment Using Thermal Sensor Auxiliary LabelsCode0
Geographical Distance Is The New Hyperparameter: A Case Study Of Finding The Optimal Pre-trained Language For English-isiZulu Machine TranslationCode0
Glo-In-One-v2: Holistic Identification of Glomerular Cells, Tissues, and Lesions in Human and Mouse HistopathologyCode0
Generalizing Few-Shot Named Entity Recognizers to Unseen Domains with Type-Related FeaturesCode0
Generalizing over Long Tail Concepts for Medical Term NormalizationCode0
Best Practices for Large-Scale, Pixel-Wise Crop Mapping and Transfer Learning WorkflowsCode0
Best of Both Worlds: Transferring Knowledge from Discriminative Learning to a Generative Visual Dialog ModelCode0
Generalized Funnelling: Ensemble Learning and Heterogeneous Document Embeddings for Cross-Lingual Text ClassificationCode0
Generalizing Teacher Networks for Effective Knowledge Distillation Across Student ArchitecturesCode0
Generalized Block-Diagonal Structure Pursuit: Learning Soft Latent Task Assignment against Negative TransferCode0
Generalization Through The Lens Of Leave-One-Out ErrorCode0
BERT WEAVER: Using WEight AVERaging to enable lifelong learning for transformer-based models in biomedical semantic search enginesCode0
Generalized Adaptive Transfer Network: Enhancing Transfer Learning in Reinforcement Learning Across DomainsCode0
General-Purpose Deep Point Cloud Feature ExtractorCode0
BERT is Not an Interlingua and the Bias of TokenizationCode0
BERT for Sentiment Analysis: Pre-trained and Fine-Tuned AlternativesCode0
BERT-Based Approach for Automating Course Articulation Matrix Construction with Explainable AICode0
Gated Domain Units for Multi-source Domain GeneralizationCode0
BertaQA: How Much Do Language Models Know About Local Culture?Code0
Synergistic Learning with Multi-Task DeepONet for Efficient PDE Problem SolvingCode0
Context selectivity with dynamic availability enables lifelong continual learningCode0
Generalizable Local Feature Pre-training for Deformable Shape AnalysisCode0
General solutions for nonlinear differential equations: a rule-based self-learning approach using deep reinforcement learningCode0
GLoMo: Unsupervisedly Learned Relational Graphs as Transferable RepresentationsCode0
Bengali Handwritten Character Classification using Transfer Learning on Deep Convolutional Neural NetworkCode0
Show:102550
← PrevPage 88 of 413Next →

Benchmark Results

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