WaiChing Sun - RankMe

29 papers A* 1Journal 28

Year	Rank	Type	Title / Venue / Authors
2025	A*	`conf`	Physics-Informed Diffusion Models. ICLR Jan-Hendrik Bastek, WaiChing Sun, Dennis M. Kochmann
2025	J	`jnl`	Towards scientific machine learning for granular material simulations - challenges and opportunities. CoRR 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
2024	J	`jnl`	A review on data-driven constitutive laws for solids. CoRR Jan Niklas Fuhg, Govinda Anantha Padmanabha, Nikolaos Bouklas, Bahador Bahmani, WaiChing Sun, Nikolaos N. Vlassis, Moritz Flaschel, Pietro Carrara, Laura De Lorenzis
2024	J	`jnl`	Neural networks meet anisotropic hyperelasticity: A framework based on generalized structure tensors and isotropic tensor functions. CoRR Karl A. Kalina, Jörg Brummund, WaiChing Sun, Markus Kästner
2024	J	`jnl`	Physics-Informed Diffusion Models. CoRR Jan-Hendrik Bastek, WaiChing Sun, Dennis M. Kochmann
2024	J	`jnl`	Viscoelasticty with physics-augmented neural networks: Model formulation and training methods without prescribed internal variables. CoRR Max Rosenkranz, Karl A. Kalina, Jörg Brummund, WaiChing Sun, Markus Kästner
2023	J	`jnl`	Denoising diffusion algorithm for inverse design of microstructures with fine-tuned nonlinear material properties. CoRR Nikolaos N. Vlassis, WaiChing Sun
2023	J	`jnl`	Discovering interpretable elastoplasticity models via the neural polynomial method enabled symbolic regressions. CoRR Bahador Bahmani, Hyoung Suk Suh, WaiChing Sun
2023	J	`jnl`	Neural network-based multiscale modeling of finite strain magneto-elasticity with relaxed convexity criteria. CoRR Karl A. Kalina, Philipp Gebhart, Jörg Brummund, Lennart Linden, WaiChing Sun, Markus Kästner
2023	J	`jnl`	Physics-constrained symbolic model discovery for polyconvex incompressible hyperelastic materials. CoRR Bahador Bahmani, WaiChing Sun
2023	J	`jnl`	Prediction of Effective Elastic Moduli of Rocks using Graph Neural Networks. CoRR Jaehong Chung, Rasool Ahmad, WaiChing Sun, Wei Cai, Tapan Mukerji
2023	J	`jnl`	Synthesizing realistic sand assemblies with denoising diffusion in latent space. CoRR Nikolaos N. Vlassis, WaiChing Sun, Khalid A. Alshibli, Richard A. Regueiro
2022	J	`jnl`	Design of experiments for the calibration of history-dependent models via deep reinforcement learning and an enhanced Kalman filter. CoRR Rubén Villarreal, Nikolaos N. Vlassis, Nhon N. Phan, Tommie A. Catanach, Reese E. Jones, Nathaniel A. Trask, Sharlotte L. B. Kramer, WaiChing Sun
2022	J	`jnl`	Geometric deep learning for computational mechanics Part II: Graph embedding for interpretable multiscale plasticity. CoRR Nikolaos N. Vlassis, WaiChing Sun
2021	J	`jnl`	A new finite element level set reinitialization method based on the shifted boundary method. J. Comput. Phys. Tianju Xue, WaiChing Sun, Sigrid Adriaenssens, Yujie Wei, Chuanqi Liu
2021	J	`jnl`	Data-driven discovery of interpretable causal relations for deep learning material laws with uncertainty propagation. CoRR Xiao Sun, Bahador Bahmani, Nikolaos N. Vlassis, WaiChing Sun, Yanxun Xu
2021	J	`jnl`	Equivariant geometric learning for digital rock physics: estimating formation factor and effective permeability tensors from Morse graph. CoRR Chen Cai, Nikolaos Vlassis, Lucas Magee, Ran Ma, Zeyu Xiong, Bahador Bahmani, Teng-Fong Wong, Yusu Wang, WaiChing Sun
2021	J	`jnl`	MD-inferred neural network monoclinic finite-strain hyperelasticity models for β-HMX: Sobolev training and validation against physical constraints. CoRR Nikolaos N. Vlassis, Puhan Zhao, Ran Ma, Tommy Sewell, WaiChing Sun
2021	J	`jnl`	Manifold embedding data-driven mechanics. CoRR Bahador Bahmani, WaiChing Sun
2021	J	`jnl`	Training multi-objective/multi-task collocation physics-informed neural network with student/teachers transfer learnings. CoRR Bahador Bahmani, WaiChing Sun
2020	J	`jnl`	A non-cooperative meta-modeling game for automated third-party calibrating, validating, and falsifying constitutive laws with parallelized adversarial attacks. CoRR Kun Wang, WaiChing Sun, Qiang Du
2020	J	`jnl`	A phase field model for cohesive fracture in micropolar continua. CoRR Hyoung Suk Suh, WaiChing Sun, Devin O'Connor
2020	J	`jnl`	An accelerated hybrid data-driven/model-based approach for poroelasticity problems with multi-fidelity multi-physics data. CoRR Bahador Bahmani, WaiChing Sun
2020	J	`jnl`	An immersed phase field fracture model for fluid-infiltrating porous media with evolving Beavers-Joseph-Saffman condition. CoRR Hyoung Suk Suh, WaiChing Sun
2020	J	`jnl`	Geometric deep learning for computational mechanics Part I: Anisotropic Hyperelasticity. CoRR Nikolaos Vlassis, Ran Ma, WaiChing Sun
2020	J	`jnl`	ILS-MPM: an implicit level-set-based material point method for frictional particulate contact mechanics of deformable particles. CoRR Chuanqi Liu, WaiChing Sun
2020	J	`jnl`	Sobolev training of thermodynamic-informed neural networks for smoothed elasto-plasticity models with level set hardening. CoRR Nikolaos N. Vlassis, WaiChing Sun
2019	J	`jnl`	A cooperative game for automated learning of elasto-plasticity knowledge graphs and models with AI-guided experimentation. CoRR Kun Wang, WaiChing Sun, Qiang Du
2018	J	`jnl`	Meta-modeling game for deriving theoretical-consistent, micro-structural-based traction-separation laws via deep reinforcement learning. CoRR Kun Wang, WaiChing Sun