15 citations · 38 across the 10 of their papers we have counts for
4 papers · 1 filter
Prediction rigidities for data-driven chemistry
Sanggyu Chong, Filippo Bigi, Federico Grasselli +3
The widespread application of machine learning (ML) to the chemical sciences is making it very important to understand how the ML models learn to correlate chemical structures with…
Adaptive energy reference for machine-learning models of the electronic density of states
Wei Bin How, Sanggyu Chong, Federico Grasselli +2
The electronic density of states (DOS) provides information regarding the distribution of electronic energy levels in a material, and can be used to approximate its optical and ele…
A prediction rigidity formalism for low-cost uncertainties in trained neural networks
Filippo Bigi, Sanggyu Chong, Michele Ceriotti +1
Regression methods are fundamental for scientific and technological applications. However, fitted models can be highly unreliable outside of their training domain, and hence the qu…
Thermal conductivity of LiPS solid electrolytes with ab initio accuracy
Davide Tisi, Federico Grasselli, Lorenzo Gigli +1
The vast amount of computational studies on electrical conduction in solid-state electrolytes is not mirrored by comparable efforts addressing thermal conduction, which has been sc…