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

@inproceedings{iclr2019_learning_28813,
  title = {{Learning deep representations by mutual information estimation and maximization}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2019},
  url = {https://iclr.cc/virtual/2019/poster/649},
}

@inproceedings{cvpr2016_cross_11457,
  title = {{Cross-Stitch Networks for Multi-Task Learning}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2016},
}

@inproceedings{neurips2016_infogan_55791,
  title = {{InfoGAN: Interpretable Representation Learning by Information Maximizing Generative Adversarial Nets}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2016},
  url = {https://nips.cc/virtual/2016/poster/7140},
}

@inproceedings{icml2019_challenging_37214,
  title = {{Challenging Common Assumptions in the Unsupervised Learning of Disentangled Representations}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2019},
  url = {https://icml.cc/virtual/2019/poster/4085},
}

@inproceedings{icml2018_disentangling_36646,
  title = {{Disentangling by Factorising}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2018},
  url = {https://icml.cc/virtual/2018/poster/2146},
}

@inproceedings{cvpr2017_split_12661,
  title = {{Split-Brain Autoencoders: Unsupervised Learning by Cross-Channel Prediction}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2017},
}

@inproceedings{aaai2021_contrastive_320,
  title = {{Contrastive Clustering}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2021},
  url = {https://aaai.org/papers/08547-contrastive-clustering/},
}

@inproceedings{cvpr2021_understanding_18074,
  title = {{Understanding the Behaviour of Contrastive Loss}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2021},
}

@inproceedings{cvpr2019_unsupervised_14974,
  title = {{Unsupervised Embedding Learning via Invariant and Spreading Instance Feature}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2019},
}

@inproceedings{cvpr2019_ocgan_14583,
  title = {{OCGAN: One-Class Novelty Detection Using GANs With Constrained Latent Representations}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2019},
}

@inproceedings{icml2019_similarity_37741,
  title = {{Similarity of Neural Network Representations Revisited}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2019},
  url = {https://icml.cc/virtual/2019/poster/4185},
}

@inproceedings{iclr2021_prototypical_30197,
  title = {{Prototypical Contrastive Learning of Unsupervised Representations}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2021},
  url = {https://iclr.cc/virtual/2021/poster/3090},
}

@inproceedings{aaai2020_learning_103909,
  title = {{Learning Attentive Pairwise Interaction for Fine-Grained Classification}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2020},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/7016},
}

@inproceedings{cvpr2020_proxy_16074,
  title = {{Proxy Anchor Loss for Deep Metric Learning}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2020},
}

@inproceedings{iclr2021_approximate_30776,
  title = {{Approximate Nearest Neighbor Negative Contrastive Learning for Dense Text Retrieval}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2021},
  url = {https://iclr.cc/virtual/2021/poster/2673},
}

@inproceedings{cvpr2020_cross_15302,
  title = {{Cross-Batch Memory for Embedding Learning}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2020},
}

@inproceedings{cvpr2017_borrowing_12090,
  title = {{Borrowing Treasures From the Wealthy: Deep Transfer Learning Through Selective Joint Fine-Tuning}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2017},
}

@inproceedings{iclr2018_a_28458,
  title = {{A Framework for the Quantitative Evaluation of Disentangled Representations}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2018},
  url = {https://iclr.cc/virtual/2018/poster/55},
}

@inproceedings{icml2019_a_37111,
  title = {{A Theoretical Analysis of Contrastive Unsupervised Representation Learning}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2019},
  url = {https://icml.cc/virtual/2019/poster/4241},
}

@inproceedings{aaai2018_structural_99818,
  title = {{Structural Deep Embedding for Hyper-Networks}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2018},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/11266},
}

@inproceedings{aaai2024_online_6847,
  title = {{Online Boosting Adaptive Learning under Concept Drift for Multistream Classification}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/29590},
}

@inproceedings{aaai2024_exploring_5914,
  title = {{Exploring Diverse Representations for Open Set Recognition}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/28385},
}

@inproceedings{aaai2024_transfer_7637,
  title = {{Transfer and Alignment Network for Generalized Category Discovery}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/28959},
}

@inproceedings{neurips2024_learning_70984,
  title = {{Learning from Teaching Regularization: Generalizable Correlations Should be Easy to Imitate}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/96222},
}

@inproceedings{aaai2024_a_5039,
  title = {{A Learnable Discrete-Prior Fusion Autoencoder with Contrastive Learning for Tabular Data Synthesis}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/29621},
}

@inproceedings{aaai2024_measuring_6618,
  title = {{Measuring Task Similarity and Its Implication in Fine-Tuning Graph Neural Networks}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/29156},
}

@inproceedings{aaai2025_usdrl_11131,
  title = {{USDRL: Unified Skeleton-Based Dense Representation Learning with Multi-Grained Feature Decorrelation}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2025},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/32899},
}

@inproceedings{neurips2024_learning_74399,
  title = {{Learning Structured Representations with Hyperbolic Embeddings}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/93170},
}

@inproceedings{aaai2024_a_5077,
  title = {{A Unified Knowledge Transfer Network for Generalized Category Discovery}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/29862},
}

@inproceedings{aaai2024_knowledge_6380,
  title = {{Knowledge Enhanced Representation Learning for Drug Discovery}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/28924},
}

@inproceedings{aaai2025_beyond_8245,
  title = {{Beyond Federated Prototype Learning: Learnable Semantic Anchors with Hyperspherical Contrast for Domain-Skewed Data}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2025},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/33829},
}

@inproceedings{iclr2024_task_35082,
  title = {{Task structure and nonlinearity jointly determine learned representational geometry}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2024},
  url = {https://iclr.cc/virtual/2024/poster/17991},
}

@inproceedings{cvpr2024_hierarchical_23697,
  title = {{Hierarchical Correlation Clustering and Tree Preserving Embedding}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2024},
  url = {https://cvpr.thecvf.com/virtual/2024/poster/30039},
}

@inproceedings{cvpr2024_riemannian_24662,
  title = {{Riemannian Multinomial Logistics Regression for SPD Neural Networks}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2024},
  url = {https://cvpr.thecvf.com/virtual/2024/poster/30661},
}

@inproceedings{cvpr2025_adapting_25438,
  title = {{Adapting to Observation Length of Trajectory Prediction via Contrastive Learning}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2025},
  url = {https://cvpr.thecvf.com/virtual/2025/poster/33118},
}

@inproceedings{cvpr2025_towards_27906,
  title = {{Towards Generalizable Trajectory Prediction using Dual-Level Representation Learning and Adaptive Prompting}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2025},
  url = {https://cvpr.thecvf.com/virtual/2025/poster/33122},
}

@inproceedings{iclr2026_on_88189,
  title = {{On the Theoretical Limitations of Embedding-Based Retrieval}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2026},
  url = {https://openreview.net/forum?id=k9CzIvzfaA},
}

@inproceedings{icml2024_how_44651,
  title = {{How Learning by Reconstruction Produces Uninformative Features For Perception}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2024},
  url = {https://icml.cc/virtual/2024/poster/33801},
}

@inproceedings{aaai2026_from_106326,
  title = {{From Points to Coalitions: Hierarchical Contrastive Shapley Values for Prioritizing Data Samples}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2026},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/38633},
}

@inproceedings{iclr2024_remasker_34164,
  title = {{ReMasker: Imputing Tabular Data with Masked Autoencoding}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2024},
  url = {https://iclr.cc/virtual/2024/poster/18911},
}