143 citations
- AstraZeneca (United Kingdom)GB2 papers
- Mila - Quebec Artificial Intelligence InstituteCA2 papers
- University of CambridgeGB2 papers
- AstraZeneca (Australia)AU1 paper
- Berlin Institute for the Foundations of Learning and DataDE1 paper
- Canadian Institute for Advanced ResearchCA1 paper
- Catholic University of Eichstätt-IngolstadtDE1 paper
- Center for Systems BiologyUS1 paper
- Centre de recherche en Epidémiologie et Santé des PopulationsFR1 paper
- Centre Inria de SaclayFR1 paper
- Chalmers University of TechnologySE1 paper
- ETH ZurichCH1 paper
14 papers
Indirect Comparisons For Health Technology Assessment: A Practical Methodological Guide And Tips With Insights From The French Transparency Commission
Louise Baschet, Ana Jarne, Matthias Monnereau +2
Context: Indirect treatment comparisons (ITC) are essential when direct head-to-head evidence is unavailable. Their reliability depends on rigorous methodological choices and caref…
Gradient-Guided Furthest Point Sampling for Robust Training Set Selection
Morris Trestman, Stefan Gugler, Felix A. Faber +1
Training set sampling methods are used to improve model performance and lower data costs in machine learning problems relevant to chemistry. We introduce Gradient Guided Furthest P…
Beyond Quantification: Navigating Uncertainty in Professional AI Systems
Sylvie Delacroix, Diana Robinson, Umang Bhatt +12
The growing integration of large language models across professional domains transforms how experts make critical decisions in healthcare, education, and law. While significant res…
Diversity-Aware Reinforcement Learning for de novo Drug Design
Hampus Gummesson Svensson, Christian Tyrchan, Ola Engkvist +1
Fine-tuning a pre-trained generative model has demonstrated good performance in generating promising drug molecules. The fine-tuning task is often formulated as a reinforcement lea…
Nonadiabatic nuclear-electron dynamics: a quantum computing approach
Arseny Kovyrshin, Mårten Skogh, Lars Tornberg +6
The combined quantum electron-nuclear dynamics is often associated with the Born-Huang expansion of the molecular wave function and the appearance of nonadiabatic effects as a pert…
Implications of Topological Imbalance for Representation Learning on Biomedical Knowledge Graphs
Stephen Bonner, Ufuk Kirik, Ola Engkvist +2
Adoption of recently developed methods from machine learning has given rise to creation of drug-discovery knowledge graphs (KG) that utilize the interconnected nature of the domain…