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 4201–4250 of 10307 papers

TitleStatusHype
Autism Spectrum Disorder Classification in Children based on Structural MRI Features Extracted using Contrastive Variational Autoencoder—0
Transfer learning for semantic similarity measures based on symbolic regressionCode0
Variational Autoencoding Molecular Graphs with Denoising Diffusion Probabilistic Model—0
Shared Growth of Graph Neural Networks via Prompted Free-direction Knowledge Distillation—0
Unified Transfer Learning Models in High-Dimensional Linear Regression—0
Scalable method for Bayesian experimental design without integrating over posterior distributionCode0
Towards the extraction of robust sign embeddings for low resource sign language recognition—0
Why does my medical AI look at pictures of birds? Exploring the efficacy of transfer learning across domain boundariesCode0
Improving the Transferability of Time Series Forecasting with Decomposition Adaptation—0
Obeying the Order: Introducing Ordered Transfer Hyperparameter OptimisationCode0
Multi-Scenario Ranking with Adaptive Feature Learning—0
Sampling weights of deep neural networksCode0
Balancing Accuracy and Training Time in Federated Learning for Violence Detection in Surveillance Videos: A Study of Neural Network Architectures—0
Transfer Learning with Semi-Supervised Dataset Annotation for Birdcall ClassificationCode0
Prediction of COVID-19 Patients' Emergency Room Revisit using Multi-Source Transfer Learning—0
A serial dual-channel library occupancy detection system based on Faster RCNN—0
Relevant Entity Selection: Knowledge Graph Bootstrapping via Zero-Shot Analogical PruningCode0
Efficient and Multiply Robust Risk Estimation under General Forms of Dataset Shift—0
Recent Advances in Optimal Transport for Machine Learning—0
Semantic Positive Pairs for Enhancing Visual Representation Learning of Instance Discrimination methods—0
Transfer Learning with Random Coefficient Ridge Regression—0
Theater Aid System for the Visually Impaired Through Transfer Learning of Spatio-Temporal Graph Convolution Networks—0
Approximated Prompt Tuning for Vision-Language Pre-trained Models—0
Transferability Metrics for Object DetectionCode0
CamemBERT-bio: Leveraging Continual Pre-training for Cost-Effective Models on French Biomedical Data—0
Differentially Private Video Activity Recognition—0
Semi-supervised Multimodal Representation Learning through a Global WorkspaceCode0
Transfer Learning across Several Centuries: Machine and Historian Integrated Method to Decipher Royal Secretary's Diary—0
Transfer: Cross Modality Knowledge Transfer using Adversarial Networks -- A Study on Gesture Recognition—0
Deep Transfer Learning for Intelligent Vehicle Perception: a Survey—0
A Collaborative Transfer Learning Framework for Cross-domain Recommendation—0
Feature Adversarial Distillation for Point Cloud Classification—0
Semi-supervised Object Detection: A Survey on Recent Research and Progress—0
A Web-based Mpox Skin Lesion Detection System Using State-of-the-art Deep Learning Models Considering Racial DiversityCode0
Cross-domain Recommender Systems via Multimodal Domain Adaptation—0
Variance-Covariance Regularization Improves Representation Learning—0
Master-ASR: Achieving Multilingual Scalability and Low-Resource Adaptation in ASR with Modular Learning—0
TaCA: Upgrading Your Visual Foundation Model with Task-agnostic Compatible AdapterCode0
Natural Language Processing in Electronic Health Records in Relation to Healthcare Decision-making: A Systematic Review—0
Transferable Curricula through Difficulty Conditioned Generators—0
Wildfire Detection Via Transfer Learning: A Survey—0
Strategies in Transfer Learning for Low-Resource Speech Synthesis: Phone Mapping, Features Input, and Source Language Selection—0
Benchmark data to study the influence of pre-training on explanation performance in MR image classification—0
Introspective Action Advising for Interpretable Transfer Learning—0
Meta-Analysis of Transfer Learning for Segmentation of Brain Lesions—0
MSVD-Indonesian: A Benchmark for Multimodal Video-Text Tasks in IndonesianCode0
EEG Decoding for Datasets with Heterogenous Electrode Configurations using Transfer Learning Graph Neural Networks—0
DynaQuant: Compressing Deep Learning Training Checkpoints via Dynamic Quantization—0
Knowledge Distillation via Token-level Relationship Graph—0
MuDPT: Multi-modal Deep-symphysis Prompt Tuning for Large Pre-trained Vision-Language ModelsCode0
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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