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

Showing 601650 of 10307 papers

TitleStatusHype
Function Encoders: A Principled Approach to Transfer Learning in Hilbert Spaces0
Distilling Knowledge for Designing Computational Imaging SystemsCode0
Fundamental Computational Limits in Pursuing Invariant Causal Prediction and Invariance-Guided Regularization0
LEKA:LLM-Enhanced Knowledge Augmentation0
Action Recognition Using Temporal Shift Module and Ensemble LearningCode0
Digital Twin Synchronization: Bridging the Sim-RL Agent to a Real-Time Robotic Additive Manufacturing Control0
Stiff Transfer Learning for Physics-Informed Neural Networks0
TAID: Temporally Adaptive Interpolated Distillation for Efficient Knowledge Transfer in Language Models0
Molecular-driven Foundation Model for Oncologic PathologyCode4
Multimodal Magic Elevating Depression Detection with a Fusion of Text and Audio Intelligence0
CoRe-Net: Co-Operational Regressor Network with Progressive Transfer Learning for Blind Radar Signal RestorationCode0
Automatic Machine Learning Framework to Study Morphological Parameters of AGN Host Galaxies within z < 1.4 in the Hyper Supreme-Cam Wide SurveyCode0
MM-Retinal V2: Transfer an Elite Knowledge Spark into Fundus Vision-Language PretrainingCode2
Transfer of Knowledge through Reverse Annealing: A Preliminary Analysis of the Benefits and What to Share0
Variational Bayesian Adaptive Learning of Deep Latent Variables for Acoustic Knowledge Transfer0
ARWKV: Pretrain is not what we need, an RNN-Attention-Based Language Model Born from TransformerCode1
Universal Image Restoration Pre-training via Degradation ClassificationCode2
Building Efficient Lightweight CNN Models0
A Transfer Learning Framework for Anomaly Detection in Multivariate IoT Traffic Data0
Expert-Free Online Transfer Learning in Multi-Agent Reinforcement LearningCode0
Cross-Modal Transfer from Memes to Videos: Addressing Data Scarcity in Hateful Video DetectionCode0
Uni-Sign: Toward Unified Sign Language Understanding at ScaleCode2
Explainable YOLO-Based Dyslexia Detection in Synthetic Handwriting Data0
In-Context Operator Learning for Linear Propagator Models0
Deep Learning-Powered Classification of Thoracic Diseases in Chest X-Rays0
Neuronal and structural differentiation in the emergence of abstract rules in hierarchically modulated spiking neural networks0
Detection and Classification of Acute Lymphoblastic Leukemia Utilizing Deep Transfer Learning0
Human Genome Book: Words, Sentences and ParagraphsCode0
Transfer Learning of Surrogate Models via Domain Affine Transformation Across Synthetic and Real-World Benchmarks0
On the Transfer of Knowledge in Quantum Algorithms0
GenTL: A General Transfer Learning Model for Building Thermal DynamicsCode0
Contrastive Representation Learning Helps Cross-institutional Knowledge Transfer: A Study in Pediatric Ventilation Management0
NUDT4MSTAR: A Large Dataset and Benchmark Towards Remote Sensing Object Recognition in the WildCode2
Bridging The Multi-Modality Gaps of Audio, Visual and Linguistic for Speech Enhancement0
Skin Disease Detection and Classification of Actinic Keratosis and Psoriasis Utilizing Deep Transfer Learning0
2-Tier SimCSE: Elevating BERT for Robust Sentence Embeddings0
WFCRL: A Multi-Agent Reinforcement Learning Benchmark for Wind Farm ControlCode1
LLM4WM: Adapting LLM for Wireless Multi-Tasking0
EchoLM: Accelerating LLM Serving with Real-time Knowledge Distillation0
Multimodal AI on Wound Images and Clinical Notes for Home Patient Referral0
A novel Trunk Branch-net PINN for flow and heat transfer prediction in porous medium0
Bidirectional Brain Image Translation using Transfer Learning from Generic Pre-trained Models0
Heterogeneous Federated Learning Systems for Time-Series Power Consumption Prediction with Multi-Head Embedding Mechanism0
Tackling Small Sample Survival Analysis via Transfer Learning: A Study of Colorectal Cancer PrognosisCode1
Heterogeneous Federated Learning System for Sparse Healthcare Time-Series Prediction0
Efficient PINNs: Multi-Head Unimodular Regularization of the Solutions Space0
Energy Consumption Reduction for UAV Trajectory Training : A Transfer Learning Approach0
How Well Do Supervised 3D Models Transfer to Medical Imaging Tasks?Code3
Rethinking Membership Inference Attacks Against Transfer Learning0
On the Adversarial Vulnerabilities of Transfer Learning in Remote Sensing0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1APCLIPAccuracy84.2Unverified
2DFA-ENTAccuracy69.2Unverified
3DFA-SAFNAccuracy69.1Unverified
4EasyTLAccuracy63.3Unverified
5MEDAAccuracy60.3Unverified
#ModelMetricClaimedVerifiedStatus
1CNN10-20% Mask PSNR3.23Unverified
#ModelMetricClaimedVerifiedStatus
1Chatterjee, Dutta et al.[1]Accuracy96.12Unverified
#ModelMetricClaimedVerifiedStatus
1Co-TuningAccuracy85.65Unverified
#ModelMetricClaimedVerifiedStatus
1Physical AccessEER5.74Unverified
#ModelMetricClaimedVerifiedStatus
1riadd.aucmediAUROC0.95Unverified