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аналитика - Physics Simulation
Learning Object Dynamics with Hierarchical Point Cloud-based Representations
A novel point-based convolutional neural network architecture is proposed to effectively learn object dynamics from 3D point cloud or mesh data, capturing both within-object and between-object interactions through specialized convolution operators and a hierarchical U-Net structure.
Vertex Block Descent: A Physics Solver for Elastic Body Dynamics with Unconditional Stability and Exceptional Performance
Vertex Block Descent introduces a physics solver for elastic body dynamics with unconditional stability and exceptional performance.
Distributed Simulation of Large Multi-body Systems: Scalability and Load Balancing Techniques
Techniques for parallelizing large rigid body simulations to achieve scalability and load balancing.
Vertex Block Descent: A Physics Solver for Elastic Body Dynamics
Vertex block descent introduces a physics solver for elastic body dynamics, offering stability, performance, and convergence.
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