350 citations · 356 across the 4 of their papers we have counts for
4 papers
Beyond Chemical 1D knowledge using Transformers
Ruud van Deursen, Igor V. Tetko, Guillaume Godin
In the present paper we evaluated efficiency of the recent Transformer-CNN models to predict target properties based on the augmented stereochemical SMILES. We selected a well-know…
State-of-the-Art Augmented NLP Transformer models for direct and single-step retrosynthesis
Igor V. Tetko, Pavel Karpov, Ruud Van Deursen +1
We investigated the effect of different training scenarios on predicting the (retro)synthesis of chemical compounds using a text-like representation of chemical reactions (SMILES)…
Multitask Learning On Graph Neural Networks Applied To Molecular Property Predictions
Fabio Capela, Vincent Nouchi, Ruud Van Deursen +2
Prediction of molecular properties, including physico-chemical properties, is a challenging task in chemistry. Herein we present a new state-of-the-art multitask prediction method…
Deep Generative Model for Sparse Graphs using Text-Based Learning with Augmentation in Generative Examination Networks
Ruud van Deursen, Guillaume Godin
Graphs and networks are a key research tool for a variety of science fields, most notably chemistry, biology, engineering and social sciences. Modeling and generation of graphs wit…