Publications

2026

1. 

   The Virtual Tissues foundation model resolves spatial proteomics across scales

   Johann Wenckstern, Eeshaan Jain, Benedikt Querfurth, and 9 more authors

   Nature, 2026

   Best Paper Award Bib PDF Code

   Best Paper Award at the ICLR 2025 Workshop on Machine Learning for Genomics Explorations (MLGenX).

   @article{wenckstern2026virtual,
     title = {{The Virtual Tissues foundation model resolves spatial proteomics across scales}},
     author = {Wenckstern, Johann and Jain, Eeshaan and von Querfurth, Benedikt and Cheng, Yexiang and Vasilev, Kiril and Pariset, Matteo and Cheng, Phil F. and Liakopoulos, Petros and Michielin, Olivier and Wicki, Andreas and Gut, Gabriele and Bunne, Charlotte},
     journal = {Nature},
     volume = {657},
     number = {8132},
     pages = {744--754},
     year = {2026},
     url = {https://www.nature.com/articles/s41586-026-10884-y},
   }

2. 

   spora: A Unified Multimodal Dataset and Platform for Spatial Proteomics

   Benedikt Querfurth, Johann Wenckstern, Eeshaan Jain, and 9 more authors

   In Advances in Neural Information Processing Systems (NeurIPS) Evaluations & Datasets (E&D) Track, 2026

   Bib Code Website

   @inproceedings{querfurth2026spora,
     title = {{spora: A Unified Multimodal Dataset and Platform for Spatial Proteomics}},
     author = {von Querfurth, Benedikt and Wenckstern, Johann and Jain, Eeshaan and Klein, Lukas and Cheng, Phil F. and Cheng, Yexiang and Vincent-Cuaz, Cédric and Frossard, Pascal and Haberecker, Martina and Wicki, Andreas and Michielin, Olivier and Bunne, Charlotte},
     booktitle = {Advances in Neural Information Processing Systems (NeurIPS) Evaluations & Datasets (E&D) Track},
     year = {2026},
     url = {https://spora.epfl.ch/},
   }

2025

1. 

   A Diffusion-Based Autoencoder for Learning Patient-Level Representations from Single-Cell Data

   Rebecca Boiarsky, Johann Wenckstern, Nicholas J. Haradhvala, and 2 more authors

   In ICML Workshop on Generative AI and Biology, 2025

   Bib PDF Code

   @inproceedings{boiarsky2025diffusion,
     title = {{A Diffusion-Based Autoencoder for Learning Patient-Level Representations from Single-Cell Data}},
     author = {Boiarsky, Rebecca and Wenckstern, Johann and Haradhvala, Nicholas J. and Getz, Gad and Sontag, David},
     booktitle = {ICML Workshop on Generative AI and Biology},
     year = {2025},
     url = {https://icml.cc/virtual/2025/51239},
   }

2. 

   Test-Time View Selection for Multi-Modal Decision Making

   Eeshaan Jain, Johann Wenckstern, Benedikt Querfurth, and 1 more author

   In ICLR Workshop on Machine Learning for Genomics Explorations (MLGenX), 2025

   Oral Presentation Bib PDF

   Oral Presentation at the ICLR 2025 Workshop on Machine Learning for Genomics Explorations (MLGenX).

   @inproceedings{jain2025testtime,
     title = {{Test-Time View Selection for Multi-Modal Decision Making}},
     author = {Jain, Eeshaan and Wenckstern, Johann and von Querfurth, Benedikt and Bunne, Charlotte},
     booktitle = {ICLR Workshop on Machine Learning for Genomics Explorations (MLGenX)},
     year = {2025},
     url = {https://iclr.cc/virtual/2025/36996},
   }

2024

1. 

   GLAudio Listens to the Sound of the Graph

   Aurelio Sulser, Johann Wenckstern, and Clara Kümpel

   In ICML Workshop on Geometry-grounded Representation Learning and Generative Modeling, 2024

   arXiv Bib PDF

   @inproceedings{sulser2024glaudio,
     title = {{GLAudio Listens to the Sound of the Graph}},
     author = {Sulser, Aurelio and Wenckstern, Johann and Kümpel, Clara},
     booktitle = {ICML Workshop on Geometry-grounded Representation Learning and Generative Modeling},
     year = {2024},
   }