5 citations · 7 across the 8 of their papers we have counts for
4 papers · 1 filter
VIANA: character Value-enhanced Intensity Assessment via domain-informed Neural Architecture
Luana P. Queiroz, Icaro S. C. Bernardes, Ana M. Ribeiro +2
Predicting the perceived intensity of odorants remains a fundamental challenge in sensory science due to the complex, non-linear behavior of their response, as well as the difficul…
Molecule Generation and Optimization for Efficient Fragrance Creation
Bruno C. L. Rodrigues, Vinicius V. Santana, Sandris Murins +1
This research introduces a Machine Learning-centric approach to replicate olfactory experiences, validated through experimental quantification of perfume perception. Key contributi…
PUFFIN: A Path-Unifying Feed-Forward Interfaced Network for Vapor Pressure Prediction
Vinicius Viena Santana, Carine Menezes Rebello, Luana P. Queiroz +3
Accurately predicting vapor pressure is vital for various industrial and environmental applications. However, obtaining accurate measurements for all compounds of interest is not p…
A nested loop for simultaneous model topology screening, parameters estimation, and identification of the optimal number of experiments: Application to a Simulated Moving Bed unit
Rodrigo V. A. Santos, Carine M. Rebello, Anderson Prudente +6
Simulated Moving Bed (SMB) chromatography is a well-known technique for the resolution of several high-value-added compounds. Parameters identification and model topology definitio…