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 5051–5100 of 10307 papers

TitleStatusHype
Transfer Learning as an Essential Tool for Digital Twins in Renewable Energy Systems—0
Adaptive Trajectory Prediction via Transferable GNN—0
Multi-Agent Policy Transfer via Task Relationship Modeling—0
Pretrained Domain-Specific Language Model for General Information Retrieval Tasks in the AEC DomainCode1
Rethinking Task Sampling for Few-shot Vision-Language Transfer LearningCode0
How many Observations are Enough? Knowledge Distillation for Trajectory Forecasting—0
Towards Inadequately Pre-trained Models in Transfer Learning—0
Unsupervised Alignment of Distributional Word Embeddings—0
HyperPELT: Unified Parameter-Efficient Language Model Tuning for Both Language and Vision-and-Language Tasks—0
A Simple Multi-Modality Transfer Learning Baseline for Sign Language TranslationCode1
Data augmentation with mixtures of max-entropy transformations for filling-level classification—0
Discriminability-Transferability Trade-Off: An Information-Theoretic PerspectiveCode0
Learning from Few Examples: A Summary of Approaches to Few-Shot Learning—0
Self-supervised learning for analysis of temporal and morphological drug effects in cancer cell imaging dataCode0
HintNet: Hierarchical Knowledge Transfer Networks for Traffic Accident Forecasting on Heterogeneous Spatio-Temporal DataCode0
Knowledge Transfer in Deep Reinforcement Learning for Slice-Aware Mobility Robustness Optimization—0
MSDN: Mutually Semantic Distillation Network for Zero-Shot LearningCode1
Generalization Through The Lens Of Leave-One-Out ErrorCode0
TIGGER: Scalable Generative Modelling for Temporal Interaction GraphsCode1
Exploration of Various Deep Learning Models for Increased Accuracy in Automatic Polyp Detection—0
Plan Your Target and Learn Your Skills: Transferable State-Only Imitation Learning via Decoupled Policy OptimizationCode0
Zero-shot Transfer Learning within a Heterogeneous Graph via Knowledge Transfer NetworksCode0
On partitioning of an SHM problem and parallels with transfer learning—0
Bridging the Source-to-target Gap for Cross-domain Person Re-Identification with Intermediate DomainsCode1
Large-Scale Hate Speech Detection with Cross-Domain TransferCode1
Hyperspectral Pixel Unmixing with Latent Dirichlet Variational Autoencoder—0
What Makes Transfer Learning Work For Medical Images: Feature Reuse & Other FactorsCode1
Transfer Learning of High-Fidelity Opacity Spectra in Autoencoders and Surrogate Models—0
X-Trans2Cap: Cross-Modal Knowledge Transfer using Transformer for 3D Dense CaptioningCode1
Visual Feature Encoding for GNNs on Road Networks—0
High-Modality Multimodal Transformer: Quantifying Modality & Interaction Heterogeneity for High-Modality Representation LearningCode1
Self-supervised Transformer for Deepfake Detection—0
Transfer Learning Algorithm with Knowledge Division LevelCode0
Self-Supervised Vision Transformers Learn Visual Concepts in HistopathologyCode1
A Versatile Agent for Fast Learning from Human Instructors—0
One Model is All You Need: Multi-Task Learning Enables Simultaneous Histology Image Segmentation and ClassificationCode1
Improving Response Time of Home IoT Services in Federated LearningCode0
A Multimodal German Dataset for Automatic Lip Reading Systems and Transfer Learning—0
TransKD: Transformer Knowledge Distillation for Efficient Semantic SegmentationCode1
BioADAPT-MRC: Adversarial Learning-based Domain Adaptation Improves Biomedical Machine Reading Comprehension TaskCode0
A Survey of Multilingual Models for Automatic Speech Recognition—0
A Deep Learning Approach for Network-wide Dynamic Traffic Prediction during Hurricane Evacuation—0
Learn From the Past: Experience Ensemble Knowledge Distillation—0
The Reality of Multi-Lingual Machine Translation—0
Towards Unsupervised Domain Adaptation via Domain-Transformer—0
Oolong: Investigating What Makes Transfer Learning Hard with Controlled StudiesCode0
Collaborative Training of Heterogeneous Reinforcement Learning Agents in Environments with Sparse Rewards: What and When to Share?Code0
A Class of Geometric Structures in Transfer Learning: Minimax Bounds and Optimality—0
Absolute Zero-Shot LearningCode0
GroupViT: Semantic Segmentation Emerges from Text SupervisionCode2
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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