| A computational workflow to study particle transport and filtration in porous media: Coupling CFD and deep learning A Marcato, G Boccardo, D Marchisio Chemical Engineering Journal 417, 128936, 2021 | 72 | 2021 |
| From computational fluid dynamics to structure interpretation via neural networks: An application to flow and transport in porous media A Marcato, G Boccardo, D Marchisio Industrial & Engineering Chemistry Research 61 (24), 8530-8541, 2022 | 45 | 2022 |
| Prediction of local concentration fields in porous media with chemical reaction using a multi scale convolutional neural network A Marcato, JE Santos, G Boccardo, H Viswanathan, D Marchisio, ... Chemical Engineering Journal 455, 140367, 2023 | 28 | 2023 |
| Modeling the 4D discharge of lithium-ion batteries with a multiscale time-dependent deep learning framework A Marcato, JE Santos, C Liu, G Boccardo, D Marchisio, AA Franco Energy Storage Materials 63, 102927, 2023 | 15 | 2023 |
| Reconciling deep learning and first‐principle modelling for the investigation of transport phenomena in chemical engineering A Marcato, D Marchisio, G Boccardo The Canadian Journal of Chemical Engineering 101 (6), 3013-3018, 2023 | 10 | 2023 |
| A computational workflow to study particle transport in porous media: coupling CFD and deep learning A Marcato, G Boccardo, DL Marchisio Computer Aided Chemical Engineering 48, 1759-1764, 2020 | 7 | 2020 |
| A diffused-interface model for the lyophilization of a packed bed of spray-frozen particles L Stratta, MB Adali, AA Barresi, G Boccardo, A Marcato, R Tuccinardi, ... Chemical Engineering Science 275, 118726, 2023 | 5 | 2023 |
| Accoppiamento di CFD e Machine Learning: due casi studio nell'ingegneria di processo= Coupling CFD and Machine Learning: two case studies in process engineering A Marcato Politecnico di Torino, 2019 | 2 | 2019 |
| Accelerating Multiphase Flow Simulations with Denoising Diffusion Model Driven Initializations J Chung, A Marcato, EJ Guiltinan, T Mukerji, H Viswanathan, YT Lin, ... arXiv preprint arXiv:2406.19333, 2024 | 1 | 2024 |
| Journey over destination: dynamic sensor placement enhances generalization A Marcato, E Guiltinan, H Viswanathan, D O’Malley, N Lubbers, JE Santos Machine Learning: Science and Technology 5 (2), 025070, 2024 | 1 | 2024 |
| Learning a general model of single phase flow in complex 3D porous media JE Santos, A Marcato, Q Kang, M Mehana, D O’Malley, H Viswanathan, ... Machine Learning: Science and Technology 5 (2), 025039, 2024 | 1 | 2024 |
| Reconstruction of Fields from Sparse Sensing: Differentiable Sensor Placement Enhances Generalization A Marcato, D O'Malley, H Viswanathan, E Guiltinan, JE Santos arXiv preprint arXiv:2312.09176, 2023 | 1 | 2023 |
| Generating Multiphase Fluid Configurations in Fractures using Diffusion Models J Chung, A Marcato, EJ Guiltinan, T Mukerji, YT Lin, JE Santos arXiv preprint arXiv:2312.04375, 2023 | 1 | 2023 |
| Enhancing Mass Transfer Coefficient Prediction from Field Emission Scanning Electron Microscope Images Through Convolutional Neural Networks and Data Augmentation Techniques A Marcato, G Boccardo, R Pisano Processes 13 (2), 365, 2025 | | 2025 |
| Accelerating multiphase simulations with denoising diffusion model driven initializations J Chung, A Marcato, EJ Guiltinan, T Mukerji, H Viswanathan, YT Lin, ... Journal of Geophysical Research: Machine Learning and Computation 1 (4 …, 2024 | | 2024 |
| Machine learned reconstruction of tsunami dynamics from sparse observations E McDugald, A Mohan, D Engwirda, A Marcato, J Santos arXiv preprint arXiv:2411.12948, 2024 | | 2024 |
| Upscaling Microscale Flow Effects in Fractures using Differentiable Programming A Marcato, D O'Malley, EJ Guiltinan, HS Viswanathan, JA Estrada Santos Los Alamos National Laboratory (LANL), Los Alamos, NM (United States), 2024 | | 2024 |
| Generating Multiphase Fluid Configurations in Fractures using Diffusion Models YT Lin, J Chung, A Marcato, EJ Guiltinan, T Mukerji, JA Estrada Santos Los Alamos National Laboratory (LANL), Los Alamos, NM (United States), 2024 | | 2024 |
| Developing a Foundation Model for Predicting Material Failure A Marcato, JE Santos, A Pachalieva, K Gao, R Hill, E Rougier, Q Kang, ... arXiv preprint arXiv:2411.08354, 2024 | | 2024 |
| A transformer-based model for grid-agnostic full-field reconstruction of tsunami waves from sparse observations E McDugald, A Mohan, D Engwirda, J Santos, A Marcato APS Division of Fluid Dynamics Meeting Abstracts, R15. 001, 2024 | | 2024 |
