A Comprehensive Survey on Transfer Learning

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A survey on transfer learning

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A survey of transfer learning

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How transferable are features in deep neural networks?

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Adversarial Discriminative Domain Adaptation

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Domain Adaptation via Transfer Component Analysis

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Learning Transferable Features with Deep Adaptation Networks

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A Survey on Deep Transfer Learning

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Deep domain confusion Maximizing for domain invariance

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Geodesic flow kernel for unsupervised domain adaptation

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Deep visual domain adaptation: A survey

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Manifold Regularization: A Geometric Framework for Learning from Labeled and Unlabeled Examples

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Transfer Feature Learning with Joint Distribution Adaptation

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Probabilistic Latent Semantic AnalysisPreprint

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Return of Frustratingly Easy Domain Adaptation

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Conditional Adversarial Domain AdaptationPreprint

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Boosting for transfer learning

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Integrating structured biological data by Kernel Maximum Mean Discrepancy

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Correcting Sample Selection Bias by Unlabeled Data

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A Generalized Representer Theorem

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Domain Adaptation for Large-Scale Sentiment Classification: A Deep Learning Approach

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Domain adaptation with structural correspondence learning

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Transfer Learning for Reinforcement Learning Domains: A Survey

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Frustratingly Easy Domain AdaptationPreprint

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Partial least squares regression and projection on latent structure regression (PLS Regression)

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Unsupervised Visual Domain Adaptation Using Subspace Alignment

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Unsupervised Domain Adaptation with Residual Transfer NetworksPreprint

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Relational learning via collective matrix factorization

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An overview of multi-task learning

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Domain adaptation for object recognition: An unsupervised approach

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Multi-view learning overview: Recent progress and new challenges

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Contrastive Adaptation Network for Unsupervised Domain Adaptation

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Semi-supervised Learning by Entropy Minimization

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A Survey on Multi-view LearningPreprint

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Transfer learning using computational intelligence: A survey

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Wasserstein Distance Guided Representation Learning for Domain Adaptation

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Instance Weighting for Domain Adaptation in NLP

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Deep Learning for Electromyographic Hand Gesture Signal Classification Using Transfer Learning

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Transferable Representation Learning with Deep Adaptation Networks

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Learning With Augmented Features for Supervised and Semi-Supervised Heterogeneous Domain Adaptation

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Transfer learning via dimensionality reduction

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Mind the Class Weight Bias: Weighted Maximum Mean Discrepancy for Unsupervised Domain Adaptation

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Balanced Distribution Adaptation for Transfer Learning

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Joint Geometrical and Statistical Alignment for Visual Domain Adaptation

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Sliced Wasserstein Discrepancy for Unsupervised Domain Adaptation

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Adaptation Regularization: A General Framework for Transfer Learning

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Frustratingly Easy Domain Adaptation

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Domain Transfer Multiple Kernel Learning

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Characterizing and Avoiding Negative Transfer

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Partial Transfer Learning with Selective Adversarial Networks

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Boosting for transfer learning with multiple sources

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Bregman Divergence-Based Regularization for Transfer Subspace Learning

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Importance Weighted Adversarial Nets for Partial Domain Adaptation

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Asymmetric Tri-training for Unsupervised Domain AdaptationPreprint

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Transfer Learning with Dynamic Adversarial Adaptation Network

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Transfer learning for activity recognition: a survey

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Transferrable Prototypical Networks for Unsupervised Domain Adaptation

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Transferability vs. Discriminability: Batch Spectral Penalization for Adversarial Domain Adaptation

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Adversarial Multiple Source Domain Adaptation

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Transfer Learning in Collaborative Filtering for Sparsity Reduction

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Co-Training for Domain Adaptation

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Nonparametric Scene Parsing via Label Transfer

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Sparse Autoencoder-Based Feature Transfer Learning for Speech Emotion Recognition

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Information-theoretic co-clustering

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A survey on heterogeneous transfer learning

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Domain-Symmetric Networks for Adversarial Domain Adaptation

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Learning with Augmented Features for Heterogeneous Domain Adaptation

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Non-invasive wearable seizure detection using long–short-term memory networks with transfer learning

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Ship Fire Detection Based on an Improved YOLO Algorithm with a Lightweight Convolutional Neural Network Model

Wu, H., Hu, Y., Wang, W., Mei, X., & Xian, J. (2022) · Sensors · doi:10.3390/s22197420 · Cited by 63 · see citing works

Establishing and evaluating trustworthy AI: overview and research challenges

Kowald, D., Scher, S., Pammer-Schindler, V., Müllner, P., Waxnegger, K., Demelius, L., Fessl, A., Toller, M., Mendoza Estrada, I. G., Šimić, I., et al. (2024) · Frontiers in Big Data · doi:10.3389/fdata.2024.1467222 · Cited by 59 · see citing works

Catastrophic Forgetting in Deep Learning: A Comprehensive Taxonomy

Aleixo, E. L., Colonna, J. G., Cristo, M., & Fernandes, E. (2023) · arXiv · doi:10.48550/arxiv.2312.10549 · Cited by 54

Catastrophic Forgetting in Deep Learning: A Comprehensive Taxonomy

Aleixo, E. L., Colonna, J. G., Cristo, M., & Fernandes, E. (2024) · Journal of the Brazilian Computer Society · doi:10.5753/jbcs.2024.3966 · Cited by 54 · see citing works

DeepFake-Adapter: Dual-Level Adapter for DeepFake Detection

Shao, R., Wu, T., Nie, L., & Liu, Z. (2025) · International Journal of Computer Vision · doi:10.1007/s11263-024-02274-6 · Cited by 48 · see citing works

A collective AI via lifelong learning and sharing at the edge

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Linking Human And Machine Behavior: A New Approach to Evaluate Training Data Quality for Beneficial Machine Learning

Hagendorff, T. (2021) · Minds and Machines · doi:10.1007/s11023-021-09573-8 · Cited by 47 · see citing works

Cross-Material Battery Capacity Estimation Using Hybrid-Model Fusion Transfer Learning

Zhao, J., Qu, X., Han, X., Wu, Y., & Burke, A. F. (2025) · Journal of Power Sources · doi:10.1016/j.jpowsour.2024.235674 · Cited by 45 · see citing works

Breathing as an Input Modality in a Gameful Breathing Training App (Breeze 2): Development and Evaluation Study

Lukic, Y. X., Teepe, G. W., Fleisch, E., & Kowatsch, T. (2022) · JMIR Serious Games · doi:10.2196/39186 · Cited by 32 · see citing works

An unsupervised domain adaptation brain CT segmentation method across image modalities and diseases

Dong, D., Fu, G., Li, J., Pei, Y., & Chen, Y. (2022) · Expert Systems with Applications · doi:10.1016/j.eswa.2022.118016 · Cited by 30 · see citing works

Towards a smarter battery management system: A critical review on deep learning-based state of charge estimation of lithium-ion batteries

Yao, J., & Kowal, J. (2025) · Energy and AI · doi:10.1016/j.egyai.2025.100585 · Cited by 30 · see citing works

DeepGhostBusters: Using Mask R-CNN to Detect and Mask Ghosting and Scattered-Light Artifacts from Optical Survey Images

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Assessment of emerging pretraining strategies in interpretable multimodal deep learning for cancer prognostication

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Data-Driven Robotic Manipulation of Cloth-like Deformable Objects: The Present, Challenges and Future Prospects

Kadi, H. A., & Terzić, K. (2023) · Sensors · doi:10.3390/s23052389 · Cited by 19 · see citing works

Reliable prediction of protein–protein binding affinity changes upon mutations with Pythia-PPI

Tao, F., Sun, J., Gao, P., Gao, G. F., & Wu, B. (2025) · National Science Review · doi:10.1093/nsr/nwaf231 · Cited by 10 · see citing works

Development and validation of a deep interpretable network for continuous acute kidney injury prediction in critically ill patients

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Transfer Learning for Angle of Arrivals Estimation in Massive MIMO System

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Robust agents learn causal world models

Richens, J., & Everitt, T. (2024) · arXiv · doi:10.48550/arxiv.2402.10877 · Cited by 5 · see citing works

Agentic Context Engineering: Evolving Contexts for Self-Improving Language Models

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ASIDS: Acoustic side-channel based intrusion detection system for industrial robotic arms

Yang, K., Zhang, Y., Li, T., & Sun, L. (2025) · Computers &amp; Security · doi:10.1016/j.cose.2025.104586 · Cited by 4 · see citing works

Multi-Source Transfer Learning Based on Inductive Knowledge-Leveraged for Medical Datasets

Zhang, J., Wu, W., & Shao, Y. (2020) · Journal of Medical Imaging and Health Informatics · doi:10.1166/jmihi.2020.3085 · Cited by 1 · see citing works

Learning to TransferPreprint

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Transfer Learning on Interstitial Lung Disease Classification

Zhi, Y., & Wang, Y. (2021) · doi:10.1109/conf-spml54095.2021.00046 · Cited by 9 · see citing works

Research on fault diagnosis model driven by artificial intelligence from domain adaptation to domain generalization

Xu, G., & Cao, Y. K. (2023) · International Conference on Artificial Intelligence and Electromechanical Automation (AIEA) · doi:10.1117/12.2684557

Transfer Learning in Motor Imagery Brain Computer Interface: A Review

Li, M., & Xu, D. (2022) · Journal of Shanghai Jiaotong University (Science) · doi:10.1007/s12204-022-2488-4 · Cited by 18 · see citing works