Search Results for author: Daniel Probst

Found 5 papers, 2 papers with code

Social and environmental impact of recent developments in machine learning on biology and chemistry research

1 code implementation1 Oct 2022 Daniel Probst

Potential societal and environmental effects such as the rapidly increasing resource use and the associated environmental impact, reproducibility issues, and exclusivity, the privatization of ML research leading to a public research brain-drain, a narrowing of the research effort caused by a focus on deep learning, and the introduction of biases through a lack of sociodemographic diversity in data and personnel caused by recent developments in machine learning are a current topic of discussion and scientific publications.

Drug Discovery

Identification of Enzymatic Active Sites with Unsupervised Language Modeling

no code implementations NeurIPS Workshop AI4Scien 2021 Loïc Kwate Dassi, Matteo Manica, Daniel Probst, Philippe Schwaller, Yves Gaetan Nana Teukam, Teodoro Laino

Herein, we apply a Transformer architecture to a language representation of bio-catalyzed chemical reactions to learn the signal at the base of the substrate-active site atomic interactions.

Language Modelling

Visualization of Very Large High-Dimensional Data Sets as Minimum Spanning Trees

no code implementations16 Aug 2019 Daniel Probst, Jean-Louis Reymond

The chemical sciences are producing an unprecedented amount of large, high-dimensional data sets containing chemical structures and associated properties.

Data Visualization

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