Carine Menezes Rebello

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Articles (16)

Collaborators (3)

Ana Ribeiro

Assistant Professor

Universidade do Porto Faculdade de Engenharia

Idelfonso B. R. Nogueira

Associate Professor

Norwegian University of Science and Technology

Alírio E. Rodrigues

University of Porto

Carine Menezes Rebello

Research Interests

Explore related searches

Contact this professor

Articles (16)

Collaborators (3)

Ana Ribeiro

Idelfonso B. R. Nogueira

Alírio E. Rodrigues

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Carine Menezes Rebello

Research Interests

Explore related searches

Contact this professor

Articles (16)

The relationship between diffusion coefficient and ion conductivity in solid-state electrolytes using feedforward neural networks and symbolic regression

Machine learning framework to predict product distribution of lignocellulosic biomass pyrolysis

Digital twins in chemical engineering: An integrated framework for identification, implementation, online learning, and uncertainty assessment

Interpretable and uncertainty-aware machine learning for trustworthy prediction in batch crystallization

Adaptive digital twin for pressure swing adsorption systems: Integrating a novel feedback tracking system, online learning and uncertainty assessment for enhanced performance

An uncertainty approach for Electric Submersible Pump modeling through Deep Neural Network

Augmented reality for chemical engineering education

Harnessing graph neural networks to craft fragrances based on consumer feedback

Optimizing CO<sub>2</sub> capture in pressure swing adsorption units: A deep neural network approach with optimality evaluation and operating maps for decision-making

PUFFIN: A path-unifying feed-forward interfaced network for vapor pressure prediction

Digital Transformation in the Chemical Industry: The Potential of Augmented Reality and Digital Twin

Interpretable Scientific Machine Learning Approach for Correcting Phenomenological Models: Methodology Validation on an ESP Prototype

Efficient hybrid modeling and sorption model discovery for non-linear advection-diffusion-sorption systems: A systematic scientific machine learning approach

Generating Flavor Molecules Using Scientific Machine Learning

A Reinforcement Learning Framework to Discover Natural Flavor Molecules

A Robust Learning Methodology for Uncertainty-Aware Scientific Machine Learning Models

Collaborators (3)

Ana Ribeiro

Idelfonso B. R. Nogueira

Alírio E. Rodrigues

How do I reach out?

Meet Kite AI