2026
- Ren Y et al. “mnDINO: Accurate and robust segmentation of micronuclei with vision transformer networks”. bioRxiv. 2026.
- Agrawal V et al. “CHAMMI-75: pre-training multi-channel models with heterogeneous microscopy images”. ICLR (International Conference on Learning Representations). 2026
- Volpe G et al. “Roadmap on deep learning for microscopy”. Journal of Physics: Photonics, 8(1). 2026.
2025
- Moutakanni T et al. “Cell-DINO: Self-supervised image-based embeddings for cell fluorescent microscopy”. PLOS Computational Biology, 21(12): e1013828. 2025.
- De Lorenci AV et al. “Scaling Channel-Adaptive Self-Supervised Learning”. Transactions on Machine Learning Research (TMLR). 2025.
- Pham C et al. “ChA-MAEViT: Unifying Channel-Aware Masked Autoencoders and Multi-Channel Vision Transformers for Improved Cross-Channel Learning”. NeurIPS (Conference on Neural Information Processing Systems). 2025.
2024
- Moshkov N et al. “Learning representations for image-based profiling of perturbations”. Nature Communications, 15: 1594. 2024.
2023
- Fonnegra R et al. “Analysis of cellular phenotypes with unbiased image-based generative models”. NeurIPS 2023 Workshop on Generative AI and Biology (GenBio). 2023.
- ZS et al. “CHAMMI: A benchmark for channel-adaptive models in microscopy imaging”. NeurIPS (Datasets and Benchmarks Track). 2023.