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 21512175 of 10307 papers

TitleStatusHype
GenTL: A General Transfer Learning Model for Building Thermal DynamicsCode0
Beyond Shared Vocabulary: Increasing Representational Word Similarities across Languages for Multilingual Machine TranslationCode0
Generating Thermal Human Faces for Physiological Assessment Using Thermal Sensor Auxiliary LabelsCode0
Generative Causal Representation Learning for Out-of-Distribution Motion ForecastingCode0
GLoMo: Unsupervisedly Learned Relational Graphs as Transferable RepresentationsCode0
Graph Few-shot Learning via Knowledge TransferCode0
Heterogeneous Treatment Effect with Trained Kernels of the Nadaraya-Watson RegressionCode0
Generalized Funnelling: Ensemble Learning and Heterogeneous Document Embeddings for Cross-Lingual Text ClassificationCode0
Generalizing Few-Shot Named Entity Recognizers to Unseen Domains with Type-Related FeaturesCode0
Beyond Labels: Empowering Human Annotators with Natural Language Explanations through a Novel Active-Learning ArchitectureCode0
Generalizing over Long Tail Concepts for Medical Term NormalizationCode0
Beyond Knowledge Silos: Task Fingerprinting for Democratization of Medical Imaging AICode0
Learning representations that are closed-form Monge mapping optimal with application to domain adaptationCode0
Generalized Adaptive Transfer Network: Enhancing Transfer Learning in Reinforcement Learning Across DomainsCode0
Generalizable Local Feature Pre-training for Deformable Shape AnalysisCode0
Generalization Through The Lens Of Leave-One-Out ErrorCode0
Generalized Block-Diagonal Structure Pursuit: Learning Soft Latent Task Assignment against Negative TransferCode0
Generalizing Teacher Networks for Effective Knowledge Distillation Across Student ArchitecturesCode0
Beyond English: Evaluating Automated Measurement of Moral Foundations in Non-English Discourse with a Chinese Case StudyCode0
Context selectivity with dynamic availability enables lifelong continual learningCode0
GAN pretraining for deep convolutional autoencoders applied to Software-based Fingerprint Presentation Attack DetectionCode0
GAN Cocktail: mixing GANs without dataset accessCode0
GANTL: Towards Practical and Real-Time Topology Optimization with Conditional GANs and Transfer LearningCode0
ABC-Former: Auxiliary Bimodal Cross-domain Transformer with Interactive Channel Attention for White BalanceCode0
Gammatonegram Representation for End-to-End Dysarthric Speech Processing Tasks: Speech Recognition, Speaker Identification, and Intelligibility AssessmentCode0
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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