MPM
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Unified sparse framework for large-scale material point method simulations
Announce Type: replace-cross Abstract: The material point method (MPM) is a hybrid particle-grid method widely used for simulating large deformation with history-dependent behavior. Standard MPM often relies on a dense background grid, which can be highly inefficient when material occupies a small fraction of the computational domain. Such sparsity is common in many large-scale problems, from geophysical mass flows over large terrain domains to visual-computing applications.
Unified sparse framework for large-scale material point method simulations
Announce Type: replace Abstract: The material point method (MPM) is a hybrid particle-grid method widely used for simulating large deformation with history-dependent behavior. Standard MPM often relies on a dense background grid, which can be highly inefficient when material occupies a small fraction of the computational domain. Such sparsity is common in many large-scale problems, from geophysical mass flows over large terrain domains to visual-computing applications.
MPMWorlds: Material-Point-Method Simulations for Inferring and Extrapolating Physical Dynamics
Announce Type: new Abstract: To study the ability to infer physical dynamics from videos and extrapolate them forward in time, we assemble a dataset of 2D Material Point Method (MPM) physical simulations covering rich physical phenomena such as deformable objects, fluids, kinetic objects, and emitters. We study code generation and video diffusion approaches on this dataset, identifying their strengths and weaknesses by varying the amount of physically relevant side information. The code...
OnlyDense: Reduced-Order Modeling for Lagrangian simulation
arXiv:2606.09065v1 Announce Type: new Abstract: In science and engineering, Lagrangian simulation methods such as Smooth Particle Hydrodynamics (SPH) or Material Point Method (MPM) are often employed to study the behavior of dynamic systems. However, these methods can be prohibitively computationally expensive, particularly when simulating multi-scale spatial or temporal phenomena, e.g., void growth and coalescence within macro-scale geometries, structural failure of spacecraft components...
Public Management Programme Puts Humans at the Centre of the AI Revolution
[The content of this article has been produced by our advertising partner.] As artificial intelligence (AI) reshapes economies, labour markets and public services, the Hong Kong University of Science and Technology (HKUST) is making a clear bet: the defining skill for tomorrow’s public leaders will not be coding, but judgment. At the helm of its Master of Public Management (MPM) programme is Programme Director Prof. Donald Low, who argues that leadership in the AI age demands more than...
Edge-directed geometric partitioning for versatile video coding
Announce Type: new Abstract: To improve the coding performance, geometric partition (GEO) was proposed for the upcoming VVC standard. GEO provides 140 partition candidates. The index of optimal GEO mode needs to be signaled explicitly.
UniPixie: Unified and Probabilistic 3D Physics Learning via Flow Matching
arXiv:2606.05399v1 Announce Type: new Abstract: Existing feed-forward networks excel at predicting a single set of physical properties from visual appearance, but this point-estimate paradigm fundamentally fails to capture the real world's inherent physical ambiguity. We address this by reframing physics prediction as a task of learning a controllable, continuous distribution of material properties. We introduce UNIPIXIE, a framework trained to predict a continuous and parameterized path of...