Physics-Informed Diffusion Models.

WaiChing Sun Columbia University, Department of Civil Engineering and Engineering Mechanics, New York, NY, USA Jan-Hendrik Bastek WaiChing Sun Dennis M. Kochmann Physics-Informed Diffusion Models. 2025 ICLR https://openreview.net/forum?id=tpYeermigp conf/iclr/2025 db/conf/iclr/iclr2025.html#BastekSK25

Marc Fransen Andreas Fürst Deepak Tunuguntla Daniel N. Wilke Benedikt Alkin Daniel Barreto Johannes Brandstetter Miguel Angel Cabrera Xinyan Fan Mengwu Guo Bram Kieskamp Krishna Kumar John Morrissey Jonathan Nuttall Jin Y. Ooi Luisa Orozco Stefanos-Aldo Papanicolopulos Tongming Qu Dingena Schott Takayuki Shuku WaiChing Sun Thomas Weinhart Dongwei Ye Hongyang Cheng Towards scientific machine learning for granular material simulations - challenges and opportunities. 2025 April abs/2504.08766 CoRR https://doi.org/10.48550/arXiv.2504.08766 db/journals/corr/corr2504.html#abs-2504-08766 streams/journals/corr

Max Rosenkranz Karl A. Kalina Jörg Brummund WaiChing Sun Markus Kästner Viscoelasticty with physics-augmented neural networks: Model formulation and training methods without prescribed internal variables. 2024 abs/2401.14270 CoRR https://doi.org/10.48550/arXiv.2401.14270 db/journals/corr/corr2401.html#abs-2401-14270

Jan-Hendrik Bastek WaiChing Sun Dennis M. Kochmann Physics-Informed Diffusion Models. 2024 abs/2403.14404 CoRR https://doi.org/10.48550/arXiv.2403.14404 db/journals/corr/corr2403.html#abs-2403-14404

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. 2024 abs/2405.03658 CoRR https://doi.org/10.48550/arXiv.2405.03658 db/journals/corr/corr2405.html#abs-2405-03658

Karl A. Kalina Jörg Brummund WaiChing Sun Markus Kästner Neural networks meet anisotropic hyperelasticity: A framework based on generalized structure tensors and isotropic tensor functions. 2024 abs/2410.03378 CoRR https://doi.org/10.48550/arXiv.2410.03378 db/journals/corr/corr2410.html#abs-2410-03378 streams/journals/corr

Nikolaos N. Vlassis WaiChing Sun Denoising diffusion algorithm for inverse design of microstructures with fine-tuned nonlinear material properties. 2023 abs/2302.12881 CoRR https://doi.org/10.48550/arXiv.2302.12881 db/journals/corr/corr2302.html#abs-2302-12881

Nikolaos N. Vlassis WaiChing Sun Khalid A. Alshibli Richard A. Regueiro Synthesizing realistic sand assemblies with denoising diffusion in latent space. 2023 abs/2306.04411 CoRR https://doi.org/10.48550/arXiv.2306.04411 db/journals/corr/corr2306.html#abs-2306-04411

Bahador Bahmani Hyoung Suk Suh WaiChing Sun Discovering interpretable elastoplasticity models via the neural polynomial method enabled symbolic regressions. 2023 abs/2307.13149 CoRR https://doi.org/10.48550/arXiv.2307.13149 db/journals/corr/corr2307.html#abs-2307-13149

Karl A. Kalina Philipp Gebhart Jörg Brummund Lennart Linden WaiChing Sun Markus Kästner Neural network-based multiscale modeling of finite strain magneto-elasticity with relaxed convexity criteria. 2023 abs/2308.16311 CoRR https://doi.org/10.48550/arXiv.2308.16311 db/journals/corr/corr2308.html#abs-2308-16311

Bahador Bahmani WaiChing Sun Physics-constrained symbolic model discovery for polyconvex incompressible hyperelastic materials. 2023 abs/2310.04286 CoRR https://doi.org/10.48550/arXiv.2310.04286 db/journals/corr/corr2310.html#abs-2310-04286

Jaehong Chung Rasool Ahmad WaiChing Sun Wei Cai Tapan Mukerji Prediction of Effective Elastic Moduli of Rocks using Graph Neural Networks. 2023 abs/2310.19274 CoRR https://doi.org/10.48550/arXiv.2310.19274 db/journals/corr/corr2310.html#abs-2310-19274

Nikolaos N. Vlassis WaiChing Sun Geometric deep learning for computational mechanics Part II: Graph embedding for interpretable multiscale plasticity. 2022 abs/2208.00246 CoRR https://doi.org/10.48550/arXiv.2208.00246 db/journals/corr/corr2208.html#abs-2208-00246

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. 2022 abs/2209.13126 CoRR https://doi.org/10.48550/arXiv.2209.13126 db/journals/corr/corr2209.html#abs-2209-13126

Tianju Xue WaiChing Sun Sigrid Adriaenssens Yujie Wei Chuanqi Liu A new finite element level set reinitialization method based on the shifted boundary method. 110360 2021 438 J. Comput. Phys. https://doi.org/10.1016/j.jcp.2021.110360 db/journals/jcphy/jcphy438.html#XueSAWL21

Chen Cai Nikolaos Vlassis Lucas Magee Ran Ma Zeyu Xiong Bahador Bahmani Teng-Fong Wong Yusu Wang 0001 WaiChing Sun Equivariant geometric learning for digital rock physics: estimating formation factor and effective permeability tensors from Morse graph. 2021 abs/2104.05608 CoRR https://arxiv.org/abs/2104.05608 db/journals/corr/corr2104.html#abs-2104-05608

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. 2021 abs/2105.09980 CoRR https://arxiv.org/abs/2105.09980 db/journals/corr/corr2105.html#abs-2105-09980

Bahador Bahmani WaiChing Sun Training multi-objective/multi-task collocation physics-informed neural network with student/teachers transfer learnings. 2021 abs/2107.11496 CoRR https://arxiv.org/abs/2107.11496 db/journals/corr/corr2107.html#abs-2107-11496

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. 2021 abs/2112.02077 CoRR https://arxiv.org/abs/2112.02077 db/journals/corr/corr2112.html#abs-2112-02077

Bahador Bahmani WaiChing Sun Manifold embedding data-driven mechanics. 2021 abs/2112.09842 CoRR https://arxiv.org/abs/2112.09842 db/journals/corr/corr2112.html#abs-2112-09842

Hyoung Suk Suh WaiChing Sun Devin O'Connor A phase field model for cohesive fracture in micropolar continua. 2020 abs/2001.01022 CoRR http://arxiv.org/abs/2001.01022 db/journals/corr/corr2001.html#abs-2001-01022

Chuanqi Liu WaiChing Sun ILS-MPM: an implicit level-set-based material point method for frictional particulate contact mechanics of deformable particles. 2020 abs/2001.02412 CoRR http://arxiv.org/abs/2001.02412 db/journals/corr/corr2001.html#abs-2001-02412

Nikolaos Vlassis Ran Ma WaiChing Sun Geometric deep learning for computational mechanics Part I: Anisotropic Hyperelasticity. 2020 abs/2001.04292 CoRR https://arxiv.org/abs/2001.04292 db/journals/corr/corr2001.html#abs-2001-04292

Kun Wang 0058 WaiChing Sun Qiang Du A non-cooperative meta-modeling game for automated third-party calibrating, validating, and falsifying constitutive laws with parallelized adversarial attacks. 2020 abs/2004.09392 CoRR https://arxiv.org/abs/2004.09392 db/journals/corr/corr2004.html#abs-2004-09392

Hyoung Suk Suh WaiChing Sun An immersed phase field fracture model for fluid-infiltrating porous media with evolving Beavers-Joseph-Saffman condition. 2020 abs/2008.11815 CoRR https://arxiv.org/abs/2008.11815 db/journals/corr/corr2008.html#abs-2008-11815

Nikolaos N. Vlassis WaiChing Sun Sobolev training of thermodynamic-informed neural networks for smoothed elasto-plasticity models with level set hardening. 2020 abs/2010.11265 CoRR https://arxiv.org/abs/2010.11265 db/journals/corr/corr2010.html#abs-2010-11265

Bahador Bahmani WaiChing Sun An accelerated hybrid data-driven/model-based approach for poroelasticity problems with multi-fidelity multi-physics data. 2020 abs/2012.00165 CoRR https://arxiv.org/abs/2012.00165 db/journals/corr/corr2012.html#abs-2012-00165

Kun Wang 0058 WaiChing Sun Qiang Du A cooperative game for automated learning of elasto-plasticity knowledge graphs and models with AI-guided experimentation. 2019 abs/1903.04307 CoRR http://arxiv.org/abs/1903.04307 db/journals/corr/corr1903.html#abs-1903-04307

Kun Wang 0058 WaiChing Sun Meta-modeling game for deriving theoretical-consistent, micro-structural-based traction-separation laws via deep reinforcement learning. 2018 abs/1810.10535 CoRR http://arxiv.org/abs/1810.10535 db/journals/corr/corr1810.html#abs-1810-10535

Sigrid Adriaenssens Rasool Ahmad Benedikt Alkin Khalid A. Alshibli Bahador Bahmani Daniel Barreto Jan-Hendrik Bastek Nikolaos Bouklas Johannes Brandstetter Jörg Brummund Miguel Angel Cabrera Chen Cai Wei Cai Pietro Carrara Thomas A. CatanachTommie A. Catanach Hongyang Cheng Jaehong Chung Qiang Du Xinyan Fan Moritz Flaschel Marc Fransen Jan Niklas Fuhg Andreas Fürst Philipp Gebhart Mengwu Guo Reese E. Jones Karl A. Kalina Markus Kästner Bram Kieskamp Dennis M. Kochmann Sharlotte L. B. Kramer Krishna Kumar Lennart Linden Chuanqi Liu Laura De Lorenzis Ran Ma Lucas Magee John Morrissey Tapan Mukerji Jonathan Nuttall Devin O'Connor Jin Y. Ooi Luisa Orozco Govinda Anantha Padmanabha Stefanos-Aldo Papanicolopulos Nhon N. Phan Tongming Qu Richard A. Regueiro Max Rosenkranz Dingena Schott Tommy Sewell Takayuki Shuku Hyoung Suk Suh Xiao Sun Nathaniel TraskNathaniel A. Trask Deepak Tunuguntla Rubén Villarreal Nikolaos VlassisNikolaos N. Vlassis Kun Wang 0058 Yusu Wang 0001 Yujie Wei Thomas Weinhart Daniel N. Wilke Teng-Fong Wong Zeyu Xiong Yanxun Xu Tianju Xue Dongwei Ye Puhan Zhao