23 citations · 23 across the 2 of their papers we have counts for
3 papers
Dual-Level Models for Physics-Informed Multi-Step Time Series Forecasting
Mahdi Nasiri, Johanna Kortelainen, Simo Särkkä
This paper develops an approach for multi-step forecasting of dynamical systems by integrating probabilistic input forecasting with physics-informed output prediction. Accurate mul…
Determination of Particle-Size Distributions from Light-Scattering Measurement Using Constrained Gaussian Process Regression
Fahime Seyedheydari, Mahdi Nasiri, Marcin Mińkowski +1
In this work, we propose a novel methodology for robustly estimating particle size distributions from optical scattering measurements using constrained Gaussian process regression.…
Physics-Informed Machine Learning for Grade Prediction in Froth Flotation
Mahdi Nasiri, Sahel Iqbal, Simo Särkkä
In this paper, physics-informed neural network models are developed to predict the concentrate gold grade in froth flotation cells. Accurate prediction of concentrate grades is imp…