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 6751–6800 of 10307 papers

TitleStatusHype
Multilingual Neural Semantic Parsing for Low-Resourced LanguagesCode0
DoubleField: Bridging the Neural Surface and Radiance Fields for High-fidelity Human Reconstruction and Rendering—0
DAMSL: Domain Agnostic Meta Score-based LearningCode0
AOSLO-net: A deep learning-based method for automatic segmentation of retinal microaneurysms from adaptive optics scanning laser ophthalmoscope images—0
A Survey on Deep Domain Adaptation for LiDAR Perception—0
MexPub: Deep Transfer Learning for Metadata Extraction from German Publications—0
SE(3)-equivariant prediction of molecular wavefunctions and electronic densities—0
Causality in Neural Networks -- An Extended Abstract—0
Bilingual Alignment Pre-Training for Zero-Shot Cross-Lingual TransferCode0
Language Embeddings for Typology and Cross-lingual Transfer LearningCode0
When Vision Transformers Outperform ResNets without Pre-training or Strong Data AugmentationsCode0
FedHealth 2: Weighted Federated Transfer Learning via Batch Normalization for Personalized Healthcare—0
SB_NITK at MEDIQA 2021: Leveraging Transfer Learning for Question Summarization in Medical Domain—0
Cooperative Multi-Agent Transfer Learning with Level-Adaptive Credit Assignment—0
Combining Weakly Supervised ML Techniques for Low-Resource NLU—0
Parallel sentences mining with transfer learning in an unsupervised setting—0
Multitask Learning for Emotionally Analyzing Sexual Abuse DisclosuresCode0
NLM at MEDIQA 2021: Transfer Learning-based Approaches for Consumer Question and Multi-Answer Summarization—0
Domain Adaptation for Arabic Cross-Domain and Cross-Dialect Sentiment Analysis from Contextualized Word EmbeddingCode0
Optum at MEDIQA 2021: Abstractive Summarization of Radiology Reports using simple BART Finetuning—0
New Domain, Major Effort? How Much Data is Necessary to Adapt a Temporal Tagger to the Voice Assistant DomainCode0
SAFFRON: tranSfer leArning For Food-disease RelatiOn extractioN—0
UCSD-Adobe at MEDIQA 2021: Transfer Learning and Answer Sentence Selection for Medical Summarization—0
Volta at SemEval-2021 Task 9: Statement Verification and Evidence Finding with Tables using TAPAS and Transfer LearningCode0
Volta at SemEval-2021 Task 6: Towards Detecting Persuasive Texts and Images using Textual and Multimodal EnsembleCode0
Translate and Classify: Improving Sequence Level Classification for English-Hindi Code-Mixed DataCode0
Transfer Learning as an Enhancement for Reconfiguration Management of Cyber-Physical Production Systems—0
Adaptive Multi-Source Causal Inference—0
Bounded logit attention: Learning to explain image classifiersCode0
A study on the plasticity of neural networks—0
How transfer learning impacts linguistic knowledge in deep NLP models?—0
Knowledge Transfer for Few-shot Segmentation of Novel White Matter Tracts—0
HIT: A Hierarchically Fused Deep Attention Network for Robust Code-mixed Language RepresentationCode0
Transfer Learning under High-dimensional Generalized Linear Models—0
Transferable Deep Reinforcement Learning Framework for Autonomous Vehicles with Joint Radar-Data Communications—0
FReTAL: Generalizing Deepfake Detection using Knowledge Distillation and Representation Learning—0
A systematic review of transfer learning based approaches for diabetic retinopathy detection—0
Deep Learning for EEG Seizure Detection in Preterm Infants—0
Audio-visual scene classification: analysis of DCASE 2021 Challenge submissions—0
A Survey on Anomaly Detection for Technical Systems using LSTM Networks—0
Risk-Aware Transfer in Reinforcement Learning using Successor Features—0
Neural Network Training Using _1-Regularization and Bi-fidelity Data—0
Investigating label suggestions for opinion mining in German Covid-19 social mediaCode0
Pattern Transfer Learning for Reinforcement Learning in Order Dispatching—0
Generative Adversarial Imitation Learning for Empathy-based AI—0
Extremely low-resource machine translation for closely related languages—0
A Modular and Transferable Reinforcement Learning Framework for the Fleet Rebalancing Problem—0
Using Early-Learning Regularization to Classify Real-World Noisy Data—0
Towards Understanding Knowledge Distillation—0
Designing ECG Monitoring Healthcare System with Federated Transfer Learning and Explainable AI—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