News
Latest updates from the AI for Oncology Lab.
New preprint about Constrained Empirical Risk Minimization
Our latest research provides an innovative solution to the challenge of enforcing constraints on deep neural networks. We reframe the constraints on a network as an ordinary risk minimization problem on a Riemannian manifold.
May 19, 2023
STAPLER: a language model to predict TCR–pMHC reactivity
Our latest paper introduces STAPLER, a cutting-edge language model that significantly enhances TCR-pMHC reactivity prediction, outperforming previous models in the field.
A deeper understanding of TCR-pMHC interactions is key to unlocking the potential of personalized immunotherapies and expanding our knowledge of the immune system.
May 1, 2023
GPU cluster expanded with gaia and galileo
We have added another 8xA6000 server (galileo) and a CPU server (gaia) to our Kosmos cluster. Kosmos now consists out of 70 GPUs, more than 1100 CPU cores, 6TB RAM and 1PB NAS.
April 24, 2023
Retrospective k-space Subsampling schemes For Deep MRI Reconstruction
In our new publication, we investigate and compare various retrospective k-space subsampling patterns and their effect on the quality of DL-based reconstructions. Our findings suggest that non-rectilinear and non-Cartesian subsampling patterns may be more suitable for DL-based reconstructions.
Jan. 24, 2023