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Found 10 papers, 2 papers with code
An Optimization Case Study for solving a Transport Robot Scheduling Problem on Quantum-Hybrid and Quantum-Inspired Hardware
We present a comprehensive case study comparing the performance of D-Waves' quantum-classical hybrid framework, Fujitsu's quantum-inspired digital annealer, and Gurobi's state-of-the-art classical solver in solving a transport robot scheduling problem.
Deep Anomaly Detection on Tennessee Eastman Process Data
Our extensive study will facilitate choosing appropriate anomaly detection methods in industrial applications.
Calibrated simplex-mapping classification
In a second step, the latent space representation of the training data is extended to the whole feature space by fitting a regression model to the transformed data.
Two-phase approaches to optimal model-based design of experiments: how many experiments and which ones?
Model-based experimental design is attracting increasing attention in chemical process engineering.
Optimization and Control
An Adaptive Algorithm based on High-Dimensional Function Approximation to obtain Optimal Designs
Based on the Kiefer-Wolfowitz Equivalence Theorem we present a novel design of experiments algorithm which computes optimal designs in a continuous design space.
Methodology Optimization and Control
Adaptive Sampling of Pareto Frontiers with Binary Constraints Using Regression and Classification
We present a novel adaptive optimization algorithm for black-box multi-objective optimization problems with binary constraints on the foundation of Bayes optimization.
CupNet -- Pruning a network for geometric data
Using data from a simulated cup drawing process, we demonstrate how the inherent geometrical structure of cup meshes can be used to effectively prune an artificial neural network in a straightforward way.
Machine Learning in Thermodynamics: Prediction of Activity Coefficients by Matrix Completion
Activity coefficients, which are a measure of the non-ideality of liquid mixtures, are a key property in chemical engineering with relevance to modeling chemical and phase equilibria as well as transport processes.
The Good, the Bad and the Ugly: Augmenting a black-box model with expert knowledge
We address a non-unique parameter fitting problem in the context of material science.
Optimized data exploration applied to the simulation of a chemical process
We propose a novel algorithm to explore such an unknown parameter space and improve its feasibility classification in an iterative way.
