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ORCIDNikolaos Vlassis
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2020 – today
- 2024
[i11]Jan Niklas Fuhg, Govinda Anantha Padmanabha, Nikolaos Bouklas, Bahador Bahmani, WaiChing Sun, Nikolaos N. Vlassis, Moritz Flaschel, Pietro Carrara, Laura De Lorenzis:
A review on data-driven constitutive laws for solids. CoRR abs/2405.03658 (2024)- [i10]Nikita Kartashov, Nikolaos N. Vlassis:
A Large Language Model and Denoising Diffusion Framework for Targeted Design of Microstructures with Commands in Natural Language. CoRR abs/2409.14473 (2024) - 2023
- [i9]Nikolaos N. Vlassis, WaiChing Sun:
Denoising diffusion algorithm for inverse design of microstructures with fine-tuned nonlinear material properties. CoRR abs/2302.12881 (2023) - [i8]Nikolaos N. Vlassis, WaiChing Sun, Khalid A. Alshibli, Richard A. Regueiro:
Synthesizing realistic sand assemblies with denoising diffusion in latent space. CoRR abs/2306.04411 (2023) - 2022
- [i7]Nikolaos N. Vlassis, WaiChing Sun:
Geometric deep learning for computational mechanics Part II: Graph embedding for interpretable multiscale plasticity. CoRR abs/2208.00246 (2022) - [i6]Rubén Villarreal, Nikolaos N. Vlassis, Nhon N. Phan, Tommie A. Catanach, Reese E. Jones
, Nathaniel A. Trask, Sharlotte L. B. Kramer, WaiChing Sun:
Design of experiments for the calibration of history-dependent models via deep reinforcement learning and an enhanced Kalman filter. CoRR abs/2209.13126 (2022) - 2021
- [b1]Nikolaos Vlassis:
Towards Trustworthy Geometric Deep Learning for Elastoplasticity. Columbia University, USA, 2021 - [i5]Chen Cai, Nikolaos Vlassis, Lucas Magee, Ran Ma, Zeyu Xiong, Bahador Bahmani, Teng-Fong Wong, Yusu Wang, WaiChing Sun:
Equivariant geometric learning for digital rock physics: estimating formation factor and effective permeability tensors from Morse graph. CoRR abs/2104.05608 (2021) - [i4]Xiao Sun, Bahador Bahmani, Nikolaos N. Vlassis, WaiChing Sun, Yanxun Xu:
Data-driven discovery of interpretable causal relations for deep learning material laws with uncertainty propagation. CoRR abs/2105.09980 (2021) - [i3]Nikolaos N. Vlassis, Puhan Zhao, Ran Ma, Tommy Sewell, WaiChing Sun:
MD-inferred neural network monoclinic finite-strain hyperelasticity models for β-HMX: Sobolev training and validation against physical constraints. CoRR abs/2112.02077 (2021) - 2020
- [i2]Nikolaos Vlassis, Ran Ma, WaiChing Sun:
Geometric deep learning for computational mechanics Part I: Anisotropic Hyperelasticity. CoRR abs/2001.04292 (2020) - [i1]Nikolaos N. Vlassis, WaiChing Sun:
Sobolev training of thermodynamic-informed neural networks for smoothed elasto-plasticity models with level set hardening. CoRR abs/2010.11265 (2020)
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