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

@inproceedings{neurips2017_protein_56598,
  title = {{Protein Interface Prediction using Graph Convolutional Networks}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2017},
  url = {https://nips.cc/virtual/2017/poster/9422},
}

@inproceedings{neurips2019_generative_58332,
  title = {{Generative Models for Graph-Based Protein Design}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2019},
  url = {https://nips.cc/virtual/2019/poster/14467},
}

@inproceedings{iclr2021_learning_29966,
  title = {{Learning from Protein Structure with Geometric Vector Perceptrons}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2021},
  url = {https://iclr.cc/virtual/2021/poster/3102},
}

@inproceedings{iclr2022_iterative_31164,
  title = {{Iterative Refinement Graph Neural Network for Antibody Sequence-Structure Co-design}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2022},
  url = {https://iclr.cc/virtual/2022/poster/6664},
}

@inproceedings{iclr2022_ontoprotein_31857,
  title = {{OntoProtein: Protein Pretraining With Gene Ontology Embedding}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2022},
  url = {https://iclr.cc/virtual/2022/poster/6505},
}

@inproceedings{aaai2024_prot2text_7018,
  title = {{Prot2Text: Multimodal Protein’s Function Generation with GNNs and Transformers}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/28948},
}

@inproceedings{neurips2016_protein_55945,
  title = {{Protein contact prediction from amino acid co-evolution using convolutional networks for graph-valued images}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2016},
  url = {https://nips.cc/virtual/2016/poster/7421},
}

@inproceedings{iclr2023_a_32062,
  title = {{A Graph Neural Network Approach to Automated Model Building in Cryo-EM Maps}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2023},
  url = {https://iclr.cc/virtual/2023/poster/12154},
}

@inproceedings{iclr2023_conditional_32427,
  title = {{Conditional Antibody Design as 3D Equivariant Graph Translation}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2023},
  url = {https://iclr.cc/virtual/2023/poster/11821},
}

@inproceedings{neurips2021_multi_61160,
  title = {{Multi-Scale Representation Learning on Proteins}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2021},
  url = {https://nips.cc/virtual/2021/poster/27595},
}

@inproceedings{iclr2021_intrinsic_30593,
  title = {{Intrinsic-Extrinsic Convolution and Pooling for Learning on 3D Protein Structures}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2021},
  url = {https://iclr.cc/virtual/2021/poster/2878},
}

@inproceedings{iclr2023_learning_32167,
  title = {{Learning Hierarchical Protein Representations via Complete 3D Graph Networks}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2023},
  url = {https://iclr.cc/virtual/2023/poster/11707},
}

@inproceedings{iclr2022_geometric_31008,
  title = {{Geometric Transformers for Protein Interface Contact Prediction}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2022},
  url = {https://iclr.cc/virtual/2022/poster/6202},
}

@inproceedings{cvpr2024_clustering_22976,
  title = {{Clustering for Protein Representation Learning}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2024},
  url = {https://cvpr.thecvf.com/virtual/2024/poster/29470},
}

@inproceedings{icml2024_equipocket_43326,
  title = {{EquiPocket: an E(3)-Equivariant Geometric Graph Neural Network for Ligand Binding Site Prediction}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2024},
  url = {https://icml.cc/virtual/2024/poster/35126},
}

@inproceedings{iclr2024_evaluating_35429,
  title = {{Evaluating Representation Learning on the Protein Structure Universe}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2024},
  url = {https://iclr.cc/virtual/2024/poster/17644},
}

@inproceedings{aaai2024_protein_7020,
  title = {{Protein 3D Graph Structure Learning for Robust Structure-Based Protein Property Prediction}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/29161},
}

@inproceedings{icml2025_boosting_47257,
  title = {{Boosting Protein Graph Representations through Static-Dynamic Fusion}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2025},
  url = {https://icml.cc/virtual/2025/poster/45332},
}

@inproceedings{neurips2023_a_69094,
  title = {{A Hierarchical Training Paradigm for Antibody Structure-sequence Co-design}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2023},
  url = {https://nips.cc/virtual/2023/poster/70783},
}

@inproceedings{neurips2024_motive_71555,
  title = {{MOTIVE: A Drug-Target Interaction Graph For Inductive Link Prediction}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/97758},
}

@inproceedings{neurips2024_asep_72060,
  title = {{AsEP: Benchmarking Deep Learning Methods for Antibody-specific Epitope Prediction}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/97702},
}

@inproceedings{iclr2025_atomsurf_81137,
  title = {{AtomSurf: Surface Representation for Learning on Protein Structures}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2025},
  url = {https://iclr.cc/virtual/2025/poster/30633},
}

@inproceedings{neurips2024_learning_70168,
  title = {{Learning Complete Protein Representation by Dynamically Coupling of Sequence and Structure}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/96915},
}

@inproceedings{aaai2025_gobert_9350,
  title = {{GoBERT: Gene Ontology Graph Informed BERT for Universal Gene Function Prediction}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2025},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/32043},
}

@inproceedings{neurips2024_learning_73459,
  title = {{Learning Superconductivity from Ordered and Disordered Material Structures}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/97553},
}

@inproceedings{neurips2025_pring_79153,
  title = {{PRING: Rethinking Protein-Protein Interaction Prediction from Pairs to Graphs}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2025},
  url = {https://openreview.net/forum?id=mHCOVlFXTw},
}

@inproceedings{iclr2025_glycanml_83487,
  title = {{GlycanML: A Multi-Task and Multi-Structure Benchmark for Glycan Machine Learning}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2025},
  url = {https://iclr.cc/virtual/2025/poster/28329},
}

@inproceedings{aaai2025_m_10079,
  title = {{M²N: A Progressive Macro-to-Micro 3D Modeling Scheme for Unveiling Drug-Target Affinity}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2025},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/32039},
}

@inproceedings{aaai2025_pscalpel_10255,
  title = {{PScalpel: A Machine Learning-based Guider for Protein Phase-Separating Behaviour Alteration}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2025},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/32065},
}

@inproceedings{icml2026_learning_54459,
  title = {{Learning the Interaction Prior for Protein-Protein Interaction Prediction: A Model-Agnostic Approach}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2026},
  url = {https://openreview.net/forum?id=p7PPMKTPJp},
}

@inproceedings{iclr2025_beyond_81096,
  title = {{Beyond Sequence: Impact of Geometric Context for RNA Property Prediction}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2025},
  url = {https://iclr.cc/virtual/2025/poster/30672},
}

@inproceedings{iclr2026_kgot_86864,
  title = {{KGOT: Unified Knowledge Graph and Optimal Transport Pseudo-Labeling for Molecule-Protein Interaction Prediction}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2026},
  url = {https://openreview.net/forum?id=UoYdZQIZWj},
}

@inproceedings{aaai2026_topology_99859,
  title = {{Topology-Enhanced and Label Correlation-Aware Model for Protein-Protein Interaction Prediction}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2026},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/36980},
}