58 citations
- University of VirginiaUS2 papers
- Advanced Imaging Research (United States)US1 paper
- Athinoula A. Martinos Center for Biomedical ImagingUS1 paper
- Auckland City HospitalNZ1 paper
- Auckland District Health BoardNZ1 paper
- Auckland University of TechnologyNZ1 paper
- Centre Hospitalier Universitaire de ToursFR1 paper
- Charlottesville Medical ResearchUS1 paper
- École Pour l'Informatique et les Techniques AvancéesFR1 paper
- Frederick National Laboratory for Cancer ResearchUS1 paper
- Homi Bhabha National InstituteIN1 paper
- Imperial College LondonGB1 paper
3 papers
stat.ML2025
Non-Negative Stiefel Approximating Flow: Orthogonalish Matrix Optimization for Interpretable Embeddings
Brian B. Avants, Nicholas J. Tustison, James R Stone
Interpretable representation learning is a central challenge in modern machine learning, particularly in high-dimensional settings such as neuroimaging, genomics, and text analysis…
q-bio.QM2025★ 2 cited
Generative diffusion model surrogates for mechanistic agent-based biological models
Tien Comlekoglu, J. Quetzalcoatl Toledo-Marín, Douglas W. DeSimone +3
Mechanistic, multicellular, agent-based models are commonly used to investigate tissue, organ, and organism-scale biology at single-cell resolution. The Cellular-Potts Model (CPM)…
eess.IV2021★ 58 cited
QU-BraTS: MICCAI BraTS 2020 Challenge on Quantifying Uncertainty in Brain Tumor Segmentation - Analysis of Ranking Scores and Benchmarking Results
Raghav Mehta, Angelos Filos, Ujjwal Baid +89
Deep learning (DL) models have provided state-of-the-art performance in various medical imaging benchmarking challenges, including the Brain Tumor Segmentation (BraTS) challenges.…