25 citations · 43 across the 8 of their papers we have counts for
12 papers
Cortical lesions, central vein sign, and paramagnetic rim lesions in multiple sclerosis: emerging machine learning techniques and future avenues
Francesco La Rosa, Maxence Wynen, Omar Al-Louzi +11
The current multiple sclerosis (MS) diagnostic criteria lack specificity, and this may lead to misdiagnosis, which remains an issue in present-day clinical practice. In addition, c…
Validation and Generalizability of Self-Supervised Image Reconstruction Methods for Undersampled MRI
Thomas Yu, Tom Hilbert, Gian Franco Piredda +8
Deep learning methods have become the state of the art for undersampled MR reconstruction. Particularly for cases where it is infeasible or impossible for ground truth, fully sampl…
FaBiAN: A Fetal Brain magnetic resonance Acquisition Numerical phantom
Hélène Lajous, Christopher W. Roy, Tom Hilbert +16
Accurate characterization of in utero human brain maturation is critical as it involves complex and interconnected structural and functional processes that may influence health lat…
Aspectuality Across Genre: A Distributional Semantics Approach
Thomas Kober, Malihe Alikhani, Matthew Stone +1
The interpretation of the lexical aspect of verbs in English plays a crucial role for recognizing textual entailment and learning discourse-level inferences. We show that two eleme…
STAR: A Schema-Guided Dialog Dataset for Transfer Learning
Johannes E. M. Mosig, Shikib Mehri, Thomas Kober
We present STAR, a schema-guided task-oriented dialog dataset consisting of 127,833 utterances and knowledge base queries across 5,820 task-oriented dialogs in 13 domains that is e…
Going Beyond T-SNE: Exposing \texttt{whatlies} in Text Embeddings
Vincent D. Warmerdam, Thomas Kober, Rachael Tatman
We introduce whatlies, an open source toolkit for visually inspecting word and sentence embeddings. The project offers a unified and extensible API with current support for a range…