| Probabilistic deep learning for real-time large deformation simulations S Deshpande, J Lengiewicz, S Bordas Computer Methods in Applied Mechanics and Engineering 398 (0045-7825), 115307, 2022 | 61* | 2022 |
| MAgNET: A Graph U-Net Architecture for Mesh-Based Simulations S Deshpande, S Bordas, J Lengiewicz Engineering Applications of Artificial Intelligence 133, 108055, 2024 | 22 | 2024 |
| Convolution, aggregation and attention based deep neural networks for accelerating simulations in mechanics S Deshpande, RI Sosa, S Bordas, J Lengiewicz Frontiers in Materials 10 (2296-8016), 2023 | 12 | 2023 |
| Data Driven Surrogate Frameworks for Computational Mechanics: Bayesian and Geometric Deep Learning Approaches S DESHPANDE Unilu-University of Luxembourg [Faculty of Science, Technology and Medicine …, 2023 | 2 | 2023 |
| Towards real-time patient-specific breast simulations: from full-field information to surrogate model A Mazier, T Lavigne, J Lengiewicz, S Deshpande, S Urcun, S Bordas 9th World Congress of Biomechanics, 2022 | 2 | 2022 |
| Graph Representation Learning Strategies for Omics Data: A Case Study on Parkinson's Disease EG de Lope, S Deshpande, RV Torné, P Liò, E Glaab, S Bordas arXiv preprint arXiv:2406.14442, 2024 | | 2024 |
| Graph Representation Learning Strategies for Omics Data: A Case Study on Parkinson's Disease E Gómez de Lope, S Deshpande, R Viñas Torné, P Liò, E Glaab, ... arXiv e-prints, arXiv: 2406.14442, 2024 | | 2024 |
| Gaussian process regression + deep neural network autoencoder for probabilistic surrogate modeling in nonlinear mechanics of solids S DESHPANDE, H RAPPEL, M Hobbs, S BORDAS, J Lengiewicz | | 2024 |
| Novel Geometric Deep Learning Surrogate Framework for Non-Linear Finite Element Simulations S Deshpande, J Lengiewicz, S Bordas The Platform for Advanced Scientific Computing (PASC23), 2023 | | 2023 |
| MAgNET: A Graph U-Net Architecture for Mesh-Based Simulations [Supplementary data] S Deshpande, S Bordas, J Lengiewicz Zenodo, 2023 | | 2023 |
| Novel deep learning approaches for learning scientific simulations S Deshpande, RI Sosa, S Bordas, J Lengiewicz The 14th International Conference of Computational Methods (ICCM), 2023 | | 2023 |
| Convolution, aggregation and attention based deep neural networks for accelerating simulations in mechanics [Dataset] S Deshpande, RI Sosa, S Bordas, J Lengiewicz Zenodo, 2023 | | 2023 |
| Real-Time Large Deformation Simulations Using Probabilistic Deep Learning Framework S Deshpande, J Lengiewicz, S Bordas The Platform for Advanced Scientific Computing (PASC22), 2022 | | 2022 |
| Real Time Hyper-elastic Simulations with Probabilistic Deep Learning S Deshpande, J Lengiewicz, S Bordas 15th World Congress on Computational Mechanics (WCCM-XV), 2022 | | 2022 |
| Real-time large deformations: A probabilistic deep learning approach S Deshpande, J Lengiewicz, S Bordas The 8th European Congress on Computational Methods in Applied Sciences and …, 2022 | | 2022 |
| Efficient Meta-modelling for the simulation of soft tissue deformations P Kerfriden, S Deshpande, E Mikaeili https://zenodo.org/record/4470106, 2021 | | 2021 |
| Data Driven Surgical Simulations S Deshpande, S Bordas, L Beex, S Cotin, A Sarkica 14th World Congress on Computational Mechanics, 2020 | | 2020 |
| DIGITAL TWINNING FOR REAL-TIME SIMULATION A Mazier, S Deshpande, S Bordas EIB Annual Economics Conference Tech Fair, 2019 | | 2019 |
STÉPHANE Pierre Alain BORDASProf. of Computational Mechanics, U. of LuxembourgVerified email at alum.northwestern.edu
