Timon Schroeter

How to Explain Individual Classification Decisions

David Baehrens, Timon Schroeter, Stefan Harmeling et al. · ArXiv.org · 2009 · 760 citations · Full text

Artificial Intelligence, Engineering, Machine Learning +24

Benchmark Data Set for in Silico Prediction of Ames Mutagenicity

Katja Hansen, Sebastian Mika, Timon Schroeter et al. · Journal of Chemical Information and Modeling · 2009 · 350 citations · Full text

Engineering, Hit Identification, Genetics +24

Applicability Domains for Classification Problems: Benchmarking of Distance to Models for Ames Mutagenicity Set

Iurii Sushko, Sergii Novotarskyi, Robert Körner et al. · Journal of Chemical Information and Modeling · 2010 · 250 citations · Full text

Accurate Solubility Prediction with Error Bars for Electrolytes:  A Machine Learning Approach

Anton Schwaighofer, Timon Schroeter, Sebastian Mika et al. · Journal of Chemical Information and Modeling · 2007 · 80 citations

Engineering, Machine Learning, Machine Learning Tool +22

Estimating the domain of applicability for machine learning QSAR models: a study on aqueous solubility of drug discovery molecules

Timon Schroeter, Anton Schwaighofer, Sebastian Mika et al. · Journal of Computer-Aided Molecular Design · 2007 · 67 citations

Medicinal Chemistry, Virtual Screening, Qsar Models +15