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 5651–5700 of 10307 papers

TitleStatusHype
Zero-Shot Physics-Guided Deep Learning for Subject-Specific MRI Reconstruction—0
Test time Adaptation through Perturbation RobustnessCode0
Learning Rich Nearest Neighbor Representations from Self-supervised Ensembles—0
CIPS-3D: A 3D-Aware Generator of GANs Based on Conditionally-Independent Pixel SynthesisCode1
Sim-to-Real Transfer in Multi-agent Reinforcement Networking for Federated Edge Computing—0
SPAP: Simultaneous Demand Prediction and Planning for Electric Vehicle Chargers in a New CityCode0
Deep Transfer Learning & Beyond: Transformer Language Models in Information Systems Research—0
Distinguishing Natural and Computer-Generated Images using Multi-Colorspace fused EfficientNetCode0
Incremental Cross-Domain Adaptation for Robust Retinopathy Screening via Bayesian Deep LearningCode0
Classical-to-Quantum Transfer Learning for Spoken Command Recognition Based on Quantum Neural Networks—0
DECAR: Deep Clustering for learning general-purpose Audio RepresentationsCode0
Schrödinger's Tree -- On Syntax and Neural Language Models—0
Cooperative Semi-Supervised Transfer Learning of Machine Reading Comprehension—0
Knowledge Inheritance for Pre-trained Language Models—0
Evaluation of Transfer Learning for Polish with a text-to-text model—0
Cross-lingual Constituency Parsing with Linguistic Typology Knowledge—0
MTG: A Benchmarking Suite for Multilingual Text Generation—0
Towards Using Diachronic Distributed Word Representations as Models of Lexical Development—0
A Variational Bayesian Approach to Learning Latent Variables for Acoustic Knowledge TransferCode0
Dataset Knowledge Transfer for Class-Incremental Learning without MemoryCode0
Lifelong Pretraining: Continually Adapting Language Models to Emerging Corpora—0
Simplest Streaming TreesCode0
Hydra: A System for Large Multi-Model Deep LearningCode1
An Acceleration Method Based on Deep Learning and Multilinear Feature Space—0
Learning Cooperation and Online Planning Through Simulation and Graph Convolutional Network—0
Malaria Parasite Detection using Efficient Neural EnsemblesCode1
Automatic Detection of COVID-19 and Pneumonia from Chest X-Ray using Deep Learning—0
SPoT: Better Frozen Model Adaptation through Soft Prompt Transfer—0
Multilingual Speech Recognition using Knowledge Transfer across Learning Processes—0
Scribosermo: Fast Speech-to-Text models for German and other LanguagesCode0
Rewire-then-Probe: A Contrastive Recipe for Probing Biomedical Knowledge of Pre-trained Language ModelsCode1
Improving Hyperparameter Optimization by Planning Ahead—0
Benchmark Problems for CEC2021 Competition on Evolutionary Transfer Multiobjectve OptimizationCode0
Domain generalization in deep learning for contrast-enhanced imaging—0
Region Semantically Aligned Network for Zero-Shot Learning—0
A Comprehensive Study on Torchvision Pre-trained Models for Fine-grained Inter-species ClassificationCode1
Composable Sparse Fine-Tuning for Cross-Lingual TransferCode1
Omni-Training: Bridging Pre-Training and Meta-Training for Few-Shot Learning—0
Self-Supervised Learning by Estimating Twin Class DistributionsCode1
MedNet: Pre-trained Convolutional Neural Network Model for the Medical Imaging Tasks—0
Finding Materialized Models for Model ReuseCode0
Winning the ICCV'2021 VALUE Challenge: Task-aware Ensemble and Transfer Learning with Visual Concepts—0
Deep Learning for Bias Detection: From Inception to Deployment—0
Swish-Driven GoogleNet for Intelligent Analog Beam Selection in Terahertz Beamspace MIMOCode0
Adapting TTS models For New Speakers using Transfer Learning—0
Detecting Damage Building Using Real-time Crowdsourced Images and Transfer LearningCode0
Småprat: DialoGPT for Natural Language Generation of Swedish Dialogue by Transfer Learning—0
Development of Deep Transformer-Based Models for Long-Term Prediction of Transient Production of Oil Wells—0
TCube: Domain-Agnostic Neural Time-series NarrationCode1
Leveraging Transformers for StarCraft Macromanagement Prediction—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