Explore
Home 
Literature 
Links 
Posts 
Molecules 
Blogs 
Zeitgeist 
Markup Help 
News 
Everything Papers Books
Ahneman et al (Reports, 13 April 2018) applied machine learning models to predict C-N cross-coupling reaction yields. The models use atomic, electronic, and vibrational descriptors as input features. However, the experimental design is insufficient to distinguish models trained on chemical features from those trained solely on random-valued features in retrospective and prospective test scenarios, thus failing classical controls in machine learning.

Posts

Let the machine learning wars commence! That’s my impression on reading over the situation I’m detailing today, at any rate. This one starts with this paper in Science, a joint effort by the Doyle group at Princeton and Merck, which used ML techniques...
Let the machine learning wars commence! That’s my impression on reading over the situation I’m detailing today, at any rate. This one starts with this paper in Science, a joint effort by the Doyle group at Princeton and Merck, which used ML techniques...