76 citations · 92 across the 6 of their papers we have counts for
6 papers
Atom-Level Optical Chemical Structure Recognition with Limited Supervision
Martijn Oldenhof, Edward De Brouwer, Adam Arany +1
Identifying the chemical structure from a graphical representation, or image, of a molecule is a challenging pattern recognition task that would greatly benefit drug development. Y…
Weakly Supervised Knowledge Transfer with Probabilistic Logical Reasoning for Object Detection
Martijn Oldenhof, Adam Arany, Yves Moreau +1
Training object detection models usually requires instance-level annotations, such as the positions and labels of all objects present in each image. Such supervision is unfortunate…
Industry-Scale Orchestrated Federated Learning for Drug Discovery
Martijn Oldenhof, Gergely Ács, Balázs Pejó +44
To apply federated learning to drug discovery we developed a novel platform in the context of European Innovative Medicines Initiative (IMI) project MELLODDY (grant n°831472), whic…
SparseChem: Fast and accurate machine learning model for small molecules
Adam Arany, Jaak Simm, Martijn Oldenhof +1
SparseChem provides fast and accurate machine learning models for biochemical applications. Especially, the package supports very high-dimensional sparse inputs, e.g., millions of…
Self-Labeling of Fully Mediating Representations by Graph Alignment
Martijn Oldenhof, Adam Arany, Yves Moreau +1
To be able to predict a molecular graph structure () given a 2D image of a chemical compound () is a challenging problem in machine learning. We are interested to learn $f: U…
ChemGrapher: Optical Graph Recognition of Chemical Compounds by Deep Learning
Martijn Oldenhof, Adam Arany, Yves Moreau +1
In drug discovery, knowledge of the graph structure of chemical compounds is essential. Many thousands of scientific articles in chemistry and pharmaceutical sciences have investig…