Nikolaos Vlassis
According to our database1,
Nikolaos Vlassis
authored at least 10 papers
between 2020 and 2023.
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Bibliography
2023
CoRR, 2023
Denoising diffusion algorithm for inverse design of microstructures with fine-tuned nonlinear material properties.
CoRR, 2023
2022
Design of experiments for the calibration of history-dependent models via deep reinforcement learning and an enhanced Kalman filter.
CoRR, 2022
Geometric deep learning for computational mechanics Part II: Graph embedding for interpretable multiscale plasticity.
CoRR, 2022
2021
MD-inferred neural network monoclinic finite-strain hyperelasticity models for β-HMX: Sobolev training and validation against physical constraints.
CoRR, 2021
Data-driven discovery of interpretable causal relations for deep learning material laws with uncertainty propagation.
CoRR, 2021
Equivariant geometric learning for digital rock physics: estimating formation factor and effective permeability tensors from Morse graph.
CoRR, 2021
2020
Sobolev training of thermodynamic-informed neural networks for smoothed elasto-plasticity models with level set hardening.
CoRR, 2020
Geometric deep learning for computational mechanics Part I: Anisotropic Hyperelasticity.
CoRR, 2020