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Found 7 papers, 1 papers with code
Neural Stress Fields for Reduced-order Elastoplasticity and Fracture
We propose a hybrid neural network and physics framework for reduced-order modeling of elastoplasticity and fracture.
Implicit Neural Spatial Representations for Time-dependent PDEs
Whereas classical solvers can dynamically adapt their spatial representation only by resorting to complex remeshing algorithms, our INSR approach is intrinsically adaptive.
CROM: Continuous Reduced-Order Modeling of PDEs Using Implicit Neural Representations
We represent this reduced manifold using continuously differentiable neural fields, which may train on any and all available numerical solutions of the continuous system, even when they are obtained using diverse methods or discretizations.
Model reduction for the material point method via an implicit neural representation of the deformation map
Our technique approximates the $\textit{kinematics}$ by approximating the deformation map using an implicit neural representation that restricts deformation trajectories to reside on a low-dimensional manifold.
Can one hear the shape of a neural network?: Snooping the GPU via Magnetic Side Channel
We find that each layer component's evaluation produces an identifiable magnetic signal signature, from which layer topology, width, function type, and sequence order can be inferred using a suitably trained classifier and a joint consistency optimization based on integer programming.
Addressing Troubles with Double Bubbles: Convergence and Stability at Multi-Bubble Junctions
In this report we discuss and propose a correction to a convergence and stability issue occurring in the work of Da et al.[2015], in which they proposed a numerical model to simulate soap bubbles.
Graphics I.3.7
Model-Driven Feed-Forward Prediction for Manipulation of Deformable Objects
A fully featured 3D model of the garment is constructed in real-time and volumetric features are then used to obtain the most similar model in the database to predict the object category and pose.
