% Key papers for Statistical transfer learning (scime atlas, https://atlas.scime.ai). Authors are not included: add them from the paper pages.

@inproceedings{cvpr2019_characterizing_13933,
  title = {{Characterizing and Avoiding Negative Transfer}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2019},
}

@inproceedings{cvpr2018_partial_13458,
  title = {{Partial Transfer Learning With Selective Adversarial Networks}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2018},
  url = {https://openaccess.thecvf.com/content_cvpr_2018/html/Cao_Partial_Transfer_Learning_CVPR_2018_paper.html},
}

@inproceedings{neurips2020_what_61099,
  title = {{What is being transferred in transfer learning?}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2020},
  url = {https://nips.cc/virtual/2020/poster/18917},
}

@inproceedings{cvpr2020_minegan_15888,
  title = {{MineGAN: Effective Knowledge Transfer From GANs to Target Domains With Few Images}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2020},
}

@inproceedings{icml2019_domain_37311,
  title = {{Domain Agnostic Learning with Disentangled Representations}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2019},
  url = {https://icml.cc/virtual/2019/poster/3571},
}

@inproceedings{icml2018_transfer_37060,
  title = {{Transfer Learning via Learning to Transfer}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2018},
  url = {https://icml.cc/virtual/2018/poster/2145},
}

@inproceedings{iclr2018_learning_28468,
  title = {{Learning to cluster in order to transfer across domains and tasks}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2018},
  url = {https://iclr.cc/virtual/2018/poster/333},
}

@inproceedings{cvpr2022_what_20216,
  title = {{What Makes Transfer Learning Work for Medical Images: Feature Reuse \& Other Factors}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2022},
}

@inproceedings{aaai2016_a_105198,
  title = {{A Representation Learning Framework for Multi-Source Transfer Parsing}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2016},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/10352},
}

@inproceedings{cvpr2022_adaptive_18266,
  title = {{Adaptive Trajectory Prediction via Transferable GNN}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2022},
}

@inproceedings{aaai2018_dual_105939,
  title = {{Dual Transfer Learning for Neural Machine Translation with Marginal Distribution Regularization}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2018},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/11999},
}

@inproceedings{cvpr2020_neural_15946,
  title = {{Neural Pose Transfer by Spatially Adaptive Instance Normalization}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2020},
}

@inproceedings{cvpr2021_in_17180,
  title = {{In the Light of Feature Distributions: Moment Matching for Neural Style Transfer}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2021},
}

@inproceedings{cvpr2021_otce_17523,
  title = {{OTCE: A Transferability Metric for Cross-Domain Cross-Task Representations}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2021},
}

@inproceedings{aaai2016_transfer_105039,
  title = {{Transfer Learning for Cross-Language Text Categorization through Active Correspondences Construction}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2016},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/10211},
}

@inproceedings{neurips2018_adapted_56835,
  title = {{Adapted Deep Embeddings: A Synthesis of Methods for k-Shot Inductive Transfer Learning}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2018},
  url = {https://nips.cc/virtual/2018/poster/11035},
}

@inproceedings{aaai2019_optimal_103502,
  title = {{Optimal Projection Guided Transfer Hashing for Image Retrieval}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2019},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/4900},
}

@inproceedings{cvpr2020_multi_15915,
  title = {{Multi-Mutual Consistency Induced Transfer Subspace Learning for Human Motion Segmentation}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2020},
}

@inproceedings{cvpr2016_constrained_11443,
  title = {{Constrained Deep Transfer Feature Learning and Its Applications}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2016},
}

@inproceedings{cvpr2022_transferability_20087,
  title = {{Transferability Metrics for Selecting Source Model Ensembles}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2022},
}

@inproceedings{aaai2025_drawing_8805,
  title = {{Drawing Informative Gradients from Sources: A One-stage Transfer Learning Framework for Cross-city Spatiotemporal Forecasting}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2025},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/32102},
}

@inproceedings{aaai2024_decoupling_5632,
  title = {{Decoupling Representation and Knowledge for Few-Shot Intent Classification and Slot Filling}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/29775},
}

@inproceedings{aaai2024_h_6170,
  title = {{H-ensemble: An Information Theoretic Approach to Reliable Few-Shot Multi-Source-Free Transfer}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/29528},
}

@inproceedings{cvpr2024_your_25305,
  title = {{Your Transferability Barrier is Fragile: Free-Lunch for Transferring the Non-Transferable Learning}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2024},
  url = {https://cvpr.thecvf.com/virtual/2024/poster/31770},
}

@inproceedings{aaai2024_da_5547,
  title = {{DA-Net: A Disentangled and Adaptive Network for Multi-Source Cross-Lingual Transfer Learning}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/29761},
}

@inproceedings{cvpr2024_structured_24904,
  title = {{Structured Model Probing: Empowering Efficient Transfer Learning by Structured Regularization}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2024},
  url = {https://cvpr.thecvf.com/virtual/2024/poster/29401},
}

@inproceedings{iclr2024_tight_35217,
  title = {{Tight Rates in Supervised Outlier Transfer Learning}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2024},
  url = {https://iclr.cc/virtual/2024/poster/17856},
}

@inproceedings{iclr2024_project_34877,
  title = {{Project and Probe: Sample-Efficient Adaptation by Interpolating Orthogonal Features}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2024},
  url = {https://iclr.cc/virtual/2024/poster/18197},
}

@inproceedings{icml2024_evolunet_44782,
  title = {{EvoluNet: Advancing Dynamic Non-IID Transfer Learning on Graphs}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2024},
  url = {https://icml.cc/virtual/2024/poster/33670},
}

@inproceedings{icml2026_domain_51016,
  title = {{Domain Transfer Becomes Identifiable via a Single Alignment}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2026},
  url = {https://openreview.net/forum?id=I6xz92EJ4T},
}

@inproceedings{icml2026_semi_53809,
  title = {{Semi-Supervised Noise Adaptation: Transferring Knowledge from Noise Domain}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2026},
  url = {https://openreview.net/forum?id=iv84rM71Mc},
}

@inproceedings{icml2026_conformal_54330,
  title = {{Conformal Calibration Transfer}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2026},
  url = {https://openreview.net/forum?id=nw5aekrzBa},
}

@inproceedings{icml2026_explaining_55223,
  title = {{Explaining Concept Shift with Interpretable Feature Attribution}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2026},
  url = {https://openreview.net/forum?id=wpKA7G7Cqu},
}

@inproceedings{neurips2025_co_76948,
  title = {{Co-Regularization Enhances Knowledge Transfer in High Dimensions}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2025},
  url = {https://openreview.net/forum?id=Oq7Rgvfqvj},
}

@inproceedings{neurips2025_wasserstein_78057,
  title = {{Wasserstein Transfer Learning}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2025},
  url = {https://openreview.net/forum?id=af9gTPce7W},
}

@inproceedings{neurips2025_a_78551,
  title = {{A High-Dimensional Statistical Method for Optimizing Transfer Quantities in Multi-Source Transfer Learning}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2025},
  url = {https://openreview.net/forum?id=fsTj0BNxyH},
}

@inproceedings{iclr2026_transfer_86330,
  title = {{Transfer Learning in Infinite Width Feature Learning Networks}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2026},
  url = {https://openreview.net/forum?id=Oox4QOhmi9},
}

@inproceedings{iclr2026_residual_87390,
  title = {{Residual Feature Integration is Sufficient to Prevent Negative Transfer}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2026},
  url = {https://openreview.net/forum?id=b1ITgc4J4M},
}

@inproceedings{aaai2026_learning_107692,
  title = {{Learning Optimal Prompt Ensemble for Multi-source Visual Prompt Transfer}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2026},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/40044},
}

@inproceedings{aaai2025_towards_11068,
  title = {{Towards Trustworthy Machine Learning Under Distribution Shifts}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2025},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/35125},
}