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 1401–1450 of 10307 papers

TitleStatusHype
Mitigating the Position Bias of Transformer Models in Passage Re-RankingCode1
Mixed formulation of physics-informed neural networks for thermo-mechanically coupled systems and heterogeneous domainsCode1
Bridging the Source-to-target Gap for Cross-domain Person Re-Identification with Intermediate DomainsCode1
MixSKD: Self-Knowledge Distillation from Mixup for Image RecognitionCode1
Domain Adaptation with Auxiliary Target Domain-Oriented ClassifierCode1
MLNet: Mutual Learning Network with Neighborhood Invariance for Universal Domain AdaptationCode1
ASSET: Robust Backdoor Data Detection Across a Multiplicity of Deep Learning ParadigmsCode1
CLIP meets GamePhysics: Towards bug identification in gameplay videos using zero-shot transfer learningCode1
Bayesian Optimization with Automatic Prior Selection for Data-Efficient Direct Policy SearchCode1
Model-Based Reinforcement Learning with Isolated ImaginationsCode1
Modeling the Distribution of Normal Data in Pre-Trained Deep Features for Anomaly DetectionCode1
Model Reprogramming: Resource-Efficient Cross-Domain Machine LearningCode1
Models Genesis: Generic Autodidactic Models for 3D Medical Image AnalysisCode1
Clinical Risk Prediction with Temporal Probabilistic Asymmetric Multi-Task LearningCode1
Modularizing Deep Learning via Pairwise Learning With KernelsCode1
CLIP-Lite: Information Efficient Visual Representation Learning with Language SupervisionCode1
Monte Carlo Tree Search based Space Transfer for Black-box OptimizationCode1
Mosaicking to Distill: Knowledge Distillation from Out-of-Domain DataCode1
MoVi: A large multi-purpose human motion and video datasetCode1
Class-relation Knowledge Distillation for Novel Class DiscoveryCode1
MSDN: Mutually Semantic Distillation Network for Zero-Shot LearningCode1
MS-Net: Multi-Site Network for Improving Prostate Segmentation with Heterogeneous MRI DataCode1
A Comprehensive Study on Torchvision Pre-trained Models for Fine-grained Inter-species ClassificationCode1
mulEEG: A Multi-View Representation Learning on EEG SignalsCode1
Multi-Aspect Transfer Learning for Detecting Low Resource Mental Disorders on Social MediaCode1
MultiCheXNet: A Multi-Task Learning Deep Network For Pneumonia-like Diseases Diagnosis From X-ray ScansCode1
Multi-domain Recommendation with Embedding Disentangling and Domain AlignmentCode1
MultiEYE: Dataset and Benchmark for OCT-Enhanced Retinal Disease Recognition from Fundus ImagesCode1
Multi-Head Distillation for Continual Unsupervised Domain Adaptation in Semantic SegmentationCode1
Benchmarking Detection Transfer Learning with Vision TransformersCode1
BuildingsBench: A Large-Scale Dataset of 900K Buildings and Benchmark for Short-Term Load ForecastingCode1
Multilingual acoustic word embedding models for processing zero-resource languagesCode1
Adapting Pre-trained Language Models to African Languages via Multilingual Adaptive Fine-TuningCode1
MultiLoKo: a multilingual local knowledge benchmark for LLMs spanning 31 languagesCode1
Classification of Large-Scale High-Resolution SAR Images with Deep Transfer LearningCode1
Multimodal Side-Tuning for Document ClassificationCode1
Multinational Address Parsing: A Zero-Shot EvaluationCode1
Multiple-Input Fourier Neural Operator (MIFNO) for source-dependent 3D elastodynamicsCode1
Bert4XMR: Cross-Market Recommendation with Bidirectional Encoder Representations from TransformerCode1
Byakto Speech: Real-time long speech synthesis with convolutional neural network: Transfer learning from English to BanglaCode1
An Empirical Analysis of Image-Based Learning Techniques for Malware ClassificationCode1
Multi-Target Adversarial Frameworks for Domain Adaptation in Semantic SegmentationCode1
Multi-Task Multi-Scale Contrastive Knowledge Distillation for Efficient Medical Image SegmentationCode1
Multi-Task Reinforcement Learning with Context-based RepresentationsCode1
PointMCD: Boosting Deep Point Cloud Encoders via Multi-view Cross-modal Distillation for 3D Shape RecognitionCode1
CleanNet: Transfer Learning for Scalable Image Classifier Training with Label NoiseCode1
Classification of animal sounds in a hyperdiverse rainforest using Convolutional Neural NetworksCode1
Classification of Epithelial Ovarian Carcinoma Whole-Slide Pathology Images Using Deep Transfer LearningCode1
An Empirical Investigation of Model-to-Model Distribution Shifts in Trained Convolutional FiltersCode1
CLiMB: A Continual Learning Benchmark for Vision-and-Language TasksCode1
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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