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Journal Articles
- 2023
[j11]Daniel Probst
:
An explainability framework for deep learning on chemical reactions exemplified by enzyme-catalysed reaction classification. J. Cheminformatics 15(1): 113 (2023)- 2021
- [j10]Philippe Schwaller, Daniel Probst, Alain C. Vaucher, Vishnu H. Nair, David Kreutter, Teodoro Laino, Jean-Louis Reymond:
Mapping the space of chemical reactions using attention-based neural networks. Nat. Mach. Intell. 3(2): 144-152 (2021) - 2020
- [j9]Daniel Probst, Jean-Louis Reymond:
Visualization of very large high-dimensional data sets as minimum spanning trees. J. Cheminformatics 12(1): 12 (2020) - [j8]Alice Capecchi, Daniel Probst, Jean-Louis Reymond:
One molecular fingerprint to rule them all: drugs, biomolecules, and the metabolome. J. Cheminformatics 12(1): 43 (2020) - 2018
- [j7]Daniel Probst, Jean-Louis Reymond:
FUn: a framework for interactive visualizations of large, high-dimensional datasets on the web. Bioinform. 34(8): 1433-1435 (2018) - [j6]Daniel Probst, Jean-Louis Reymond:
A probabilistic molecular fingerprint for big data settings. J. Cheminformatics 10(1): 66:1-66:12 (2018) - [j5]Daniel Probst, Jean-Louis Reymond:
SmilesDrawer: Parsing and Drawing SMILES-Encoded Molecular Structures Using Client-Side JavaScript. J. Chem. Inf. Model. 58(1): 1-7 (2018) - [j4]Daniel Probst, Jean-Louis Reymond:
Exploring DrugBank in Virtual Reality Chemical Space. J. Chem. Inf. Model. 58(9): 1731-1735 (2018) - 2017
- [j3]Mahendra Awale, Daniel Probst, Jean-Louis Reymond:
WebMolCS: A Web-Based Interface for Visualizing Molecules in Three-Dimensional Chemical Spaces. J. Chem. Inf. Model. 57(4): 643-649 (2017) - 2004
- [j2]Val E. Lambson, Daniel Probst:
Learning by matching patterns. Games Econ. Behav. 46(2): 398-409 (2004) - 1999
- [j1]Daniel Probst:
Evolutionary Game Theory by Jörgen Weibull. J. Artif. Soc. Soc. Simul. 2(1) (1999)
Conference and Workshop Papers
- 2007
- [c1]Klaus Thiel, Daniel Probst:
An Early-Warning System to Support Activities in the Management of Customer Equity and How to Obtain the Most from Spatial Customer Equity Potentials. GfKl 2007: 479-487
Informal and Other Publications
- 2022
- [i4]Daniel Probst:
Social and environmental impact of recent developments in machine learning on biology and chemistry research. CoRR abs/2210.00356 (2022) - 2021
- [i3]Opeoluwa Owoyele, Pinaki Pal, Alvaro Vidal Torreira, Daniel Probst, Matthew Shaxted, Michael Wilde, Peter Kelly Senecal:
An automated machine learning-genetic algorithm (AutoML-GA) approach for efficient simulation-driven engine design optimization. CoRR abs/2101.02653 (2021) - 2020
- [i2]Philippe Schwaller, Daniel Probst, Alain C. Vaucher, Vishnu H. Nair, David Kreutter, Teodoro Laino, Jean-Louis Reymond:
Mapping the Space of Chemical Reactions Using Attention-Based Neural Networks. CoRR abs/2012.06051 (2020) - 2019
- [i1]Daniel Probst, Jean-Louis Reymond:
Visualization of Very Large High-Dimensional Data Sets as Minimum Spanning Trees. CoRR abs/1908.10410 (2019)
Coauthor Index
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