22 citations · 37 across the 4 of their papers we have counts for
4 papers
Integer linear programming for unsupervised training set selection in molecular machine learning
Matthieu Haeberle, Puck van Gerwen, Ruben Laplaza +4
Integer linear programming (ILP) is an elegant approach to solve linear optimization problems, naturally described using integer decision variables. Within the context of physics-i…
3DReact: Geometric deep learning for chemical reactions
Puck van Gerwen, Ksenia R. Briling, Charlotte Bunne +4
Geometric deep learning models, which incorporate the relevant molecular symmetries within the neural network architecture, have considerably improved the accuracy and data efficie…
Assessing the persistence of chalcogen bonds in solution with neural network potentials
Veronika Juraskova, Frederic Celerse, Ruben Laplaza +1
Non-covalent bonding patterns are commonly harvested as a design principle in the field of catalysis, supramolecular chemistry and functional materials to name a few. Yet, their co…
Overcoming Distrust in Solid State Simulations: Adding Error Bars to Computational Data
Francesca Peccati, Rubén Laplaza, Julia Contreras-García
Simulation techniques are providing with each passing day a deeper insight into the structure and properties of materials. Two main obstacles appear for the cooperation of simulati…