T
Timothy Hopper
Researcher at Amgen
Publications - 5
Citations - 1138
Timothy Hopper is an academic researcher from Amgen. The author has contributed to research in topics: Graph (abstract data type) & Artificial neural network. The author has an hindex of 5, co-authored 5 publications receiving 456 citations.
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Journal ArticleDOI
Analyzing Learned Molecular Representations for Property Prediction.
Kevin Yang,Kyle Swanson,Wengong Jin,Connor W. Coley,Philipp Eiden,Hua Gao,Angel Guzman-Perez,Timothy Hopper,Brian Kelley,Miriam Mathea,Andrew Palmer,Volker Settels,Tommi S. Jaakkola,Klavs F. Jensen,Regina Barzilay +14 more
TL;DR: In this article, a graph convolutional model that consistently matches or outperforms models using fixed molecular descriptors as well as previous graph neural architectures on both public and proprietary data sets is presented.
Posted Content
Analyzing Learned Molecular Representations for Property Prediction
Kevin Yang,Kyle Swanson,Wengong Jin,Connor W. Coley,Philipp Eiden,Hua Gao,Angel Guzman-Perez,Timothy Hopper,Brian Kelley,Miriam Mathea,Andrew Palmer,Volker Settels,Tommi S. Jaakkola,Klavs F. Jensen,Regina Barzilay +14 more
TL;DR: A graph convolutional model is introduced that consistently matches or outperforms models using fixed molecular descriptors as well as previous graph neural architectures on both public and proprietary data sets.
Journal ArticleDOI
Correction to Analyzing Learned Molecular Representations for Property Prediction.
Kevin Yang,Kyle Swanson,Wengong Jin,Connor W. Coley,Philipp Eiden,Hua Gao,Angel Guzman-Perez,Timothy Hopper,Brian Kelley,Miriam Mathea,Andrew Palmer,Volker Settels,Tommi S. Jaakkola,Klavs F. Jensen,Regina Barzilay +14 more
TL;DR: Property Prediction Kevin Yang,*, Kyle Swanson,*,† Wengong Jin,† Connor Coley,‡ Philipp Eiden, Hua Gao, Angel Guzman-Perez, Timothy Hopper, Brian Kelley, Miriam Mathea, Andrew Palmer, Volker Settels, Tommi Jaakkola and Regina Barzilay.
Posted Content
Are Learned Molecular Representations Ready For Prime Time
Kevin Yang,Kyle Swanson,Wengong Jin,Connor W. Coley,Philipp Eiden,Hua Gao,Angel Guzman-Perez,Timothy Hopper,Brian Kelley,Miriam Mathea,Andrew Palmer,Volker Settels,Tommi S. Jaakkola,Klavs F. Jensen,Regina Barzilay +14 more
TL;DR: A graph convolutional model is introduced that consistently outperforms models using fixed molecular descriptors as well as previous graph neural architectures on both public and proprietary datasets.
Posted ContentDOI
Are Learned Molecular Representations Ready for Prime Time
Kevin Yang,Kyle Swanson,Wengong Jin,Connor W. Coley,Philipp Eiden,Hua Gao,Angel Guzman-Perez,Timothy Hopper,Brian Kelley,Miriam Mathea,Andrew Palmer,Volker Settels,Tommi S. Jaakkola,Klavs F. Jensen,Regina Barzilay +14 more
TL;DR: In this article, a graph convolutional neural network (GCNN) was proposed for molecular property prediction in industrial workflows and compared with existing graph neural network architectures on both public and proprietary datasets.