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 5601–5650 of 10307 papers

TitleStatusHype
DOCKSTRING: easy molecular docking yields better benchmarks for ligand designCode1
Domain Agnostic Few-Shot Learning For Document Intelligence—0
AI-Powered Semantic Segmentation and Fluid Volume Calculation of Lung CT images in Covid-19 Patients—0
A deep convolutional neural network for classification of Aedes albopictus mosquitoes—0
Successor Feature Representations—0
Generating Table Vector Representations—0
Deep Learning Analysis of Cardiac MRI in Legacy Datasets: Multi-Ethnic Study of Atherosclerosis—0
Pay attention to emoji: Feature Fusion Network with EmoGraph2vec Model for Sentiment Analysis—0
OpeNPDN: A Neural-network-based Framework for Power Delivery Network Synthesis—0
Mosaicking to Distill: Knowledge Distillation from Out-of-Domain DataCode1
Deep Transfer Learning for Multi-source Entity Linkage via Domain AdaptationCode0
Meta-Knowledge Transfer for Inductive Knowledge Graph EmbeddingCode1
Algorithmic encoding of protected characteristics in image-based models for disease detectionCode1
NIDA-CLIFGAN: Natural Infrastructure Damage Assessment through Efficient Classification Combining Contrastive Learning, Information Fusion and Generative Adversarial Networks—0
Revisit Multimodal Meta-Learning through the Lens of Multi-Task LearningCode0
Transfer learning with causal counterfactual reasoning in Decision Transformers—0
Deep Integrated Pipeline of Segmentation Guided Classification of Breast Cancer from Ultrasound Images—0
AVocaDo: Strategy for Adapting Vocabulary to Downstream DomainCode1
Improving the efficacy of Deep Learning models for Heart Beat detection on heterogeneous datasetsCode0
BioIE: Biomedical Information Extraction with Multi-head Attention Enhanced Graph Convolutional Network—0
A Metalearning Approach for Physics-Informed Neural Networks (PINNs): Application to Parameterized PDEs—0
Modular Gaussian Processes for Transfer LearningCode1
Zero-Shot Action Recognition from Diverse Object-Scene CompositionsCode0
Transferring Domain-Agnostic Knowledge in Video Question Answering—0
YOLO-ReT: Towards High Accuracy Real-time Object Detection on Edge GPUsCode1
Unified Instance and Knowledge Alignment Pretraining for Aspect-based Sentiment AnalysisCode1
Covariance-Generalized Matching Component Analysis for Data Fusion and Transfer Learning—0
Self-Supervised Knowledge Transfer via Loosely Supervised Auxiliary Tasks—0
Age and Gender Prediction using Deep CNNs and Transfer Learning—0
A Deep Reinforcement Learning Approach for Audio-based Navigation and Audio Source Localization in Multi-speaker Environments—0
Novel coronavirus pneumonia lesion segmentation in CT images—0
Latent-Insensitive autoencoders for Anomaly Detection—0
Review-Based Domain Disentanglement without Duplicate Users or Contexts for Cross-Domain Recommendation—0
Domain Adaptation via Maximizing Surrogate Mutual InformationCode0
Group-disentangled Representation Learning with Weakly-Supervised Regularization—0
Benchmarking of Lightweight Deep Learning Architectures for Skin Cancer Classification using ISIC 2017 Dataset—0
AFEC: Active Forgetting of Negative Transfer in Continual LearningCode1
Parametric Variational Linear Units (PVLUs) in Deep Convolutional Networks—0
Logical Activation Functions: Logit-space equivalents of Probabilistic Boolean Operators—0
Domain Adaptation and Active Learning for Fine-Grained Recognition in the Field of Biodiversity—0
Multimodal-Boost: Multimodal Medical Image Super-Resolution using Multi-Attention Network with Wavelet Transform—0
Augmenting Knowledge Distillation With Peer-To-Peer Mutual Learning For Model Compression—0
One-Shot Transfer Learning of Physics-Informed Neural NetworksCode1
Bristle: Decentralized Federated Learning in Byzantine, Non-i.i.d. Environments—0
StyleAlign: Analysis and Applications of Aligned StyleGAN ModelsCode1
CLOOB: Modern Hopfield Networks with InfoLOOB Outperform CLIPCode1
Knowledge-Guided Multiview Deep Curriculum Learning for Elbow Fracture ClassificationCode0
Text-Based Person Search with Limited DataCode1
Few-Shot Temporal Action Localization with Query Adaptive TransformerCode1
Improved Multilingual Language Model Pretraining for Social Media Text via Translation Pair PredictionCode0
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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