Guillaume Godin

According to our database, Guillaume Godin authored at least 13 papers between 2018 and 2025.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2025

Z-Error Loss for Training Neural Networks.

Guillaume Godin

CoRR, June, 2025

All You Need Is Synthetic Task Augmentation.

Guillaume Godin

CoRR, May, 2025

2024

Be aware of overfitting by hyperparameter optimization!

Igor V. Tetko, Ruud van Deursen, Guillaume Godin

J. Cheminformatics, December, 2024

2020

Transformer-CNN: Swiss knife for QSAR modeling and interpretation.

Pavel Karpov, Guillaume Godin, Igor V. Tetko

J. Cheminformatics, 2020

GEN: highly efficient SMILES explorer using autodidactic generative examination networks.

Ruud van Deursen, Peter Ertl, Igor V. Tetko, Guillaume Godin

J. Cheminformatics, 2020

Beyond Chemical 1D knowledge using Transformers.

Ruud van Deursen, Igor V. Tetko, Guillaume Godin

CoRR, 2020

Augmented Transformer Achieves 97% and 85% for Top5 Prediction of Direct and Classical Retro-Synthesis.

Igor V. Tetko, Pavel Karpov, Ruud van Deursen, Guillaume Godin

CoRR, 2020

2019

Transformer-CNN: Fast and Reliable tool for QSAR.

Pavel Karpov, Guillaume Godin, Igor V. Tetko

CoRR, 2019

Multitask Learning On Graph Neural Networks Applied To Molecular Property Predictions.

Fabio Capela, Vincent Nouchi, Ruud van Deursen, Igor V. Tetko, Guillaume Godin

CoRR, 2019

Deep Generative Model for Sparse Graphs using Text-Based Learning with Augmentation in Generative Examination Networks.

Ruud van Deursen, Guillaume Godin

CoRR, 2019

Augmentation Is What You Need!

Igor V. Tetko, Pavel Karpov, Eric Bruno, Talia B. Kimber, Guillaume Godin

Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2019 - 28th International Conference on Artificial Neural Networks, Munich, Germany, September 17-19, 2019, Proceedings, 2019

A Transformer Model for Retrosynthesis.

Pavel Karpov, Guillaume Godin, Igor V. Tetko

Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2019 - 28th International Conference on Artificial Neural Networks, Munich, Germany, September 17-19, 2019, Proceedings, 2019

2018

Synergy Effect between Convolutional Neural Networks and the Multiplicity of SMILES for Improvement of Molecular Prediction.

Talia B. Kimber, Sebastian Engelke, Igor V. Tetko, Eric Bruno, Guillaume Godin

CoRR, 2018