1 citations · 1 across the 10 of their papers we have counts for
11 papers
ASAP: Amortized Doubly-Stochastic Attention via Sliced Dual Projection
Huy Tran, Max Milkert, David Hyde
Doubly-stochastic attention has emerged as a transport-based alternative to row-softmax attention, with recent Transformer variants using it to reduce attention sinks and rank coll…
STA-FEM: Exact Streaming Assembly for Preplanned Dynamic Tetrahedral Topology Edits
Manish Acharya, David Hyde
Dynamic tetrahedral simulation pipelines rebuild topology-dependent solver state after every fracture, refinement, or merge event - discarding structural continuity that survives e…
On the Structural Failure of Chamfer Distance in 3D Shape Optimization
Chang-Yong Song, David Hyde
Chamfer distance is the standard training loss for point cloud reconstruction, completion, and generation, yet directly optimizing it can produce worse Chamfer values than not opti…
CulinaryCut-VLAP: A Vision-Language-Action-Physics Framework for Food Cutting via a Force-Aware Material Point Method
Hyunseo Koh, Chang-Yong Song, Youngjae Choi +3
Food cutting is a highly practical yet underexplored application at the intersection of vision and robotic manipulation. The task remains challenging because interactions between t…
PhysMorph-GS: Render-Guided Volumetric Morphing with Differentiable Physics
Chang-Yong Song, David Hyde
Differentiable particle-based simulation can produce physically plausible motion, but target-driven volumetric shape morphing remains underconstrained: physics-only mass matching c…
Efficient Sliced Wasserstein Distance Computation via Adaptive Bayesian Optimization
Manish Acharya, David Hyde
The sliced Wasserstein distance (SW) reduces optimal transport on to a sum of one-dimensional projections, and thanks to this efficiency, it is widely used in geomet…
Building Machine Learning Challenges for Anomaly Detection in Science
Elizabeth G. Campolongo, Yuan-Tang Chou, Ekaterina Govorkova +148
Scientific discoveries are often made by finding a pattern or object that was not predicted by the known rules of science. Oftentimes, these anomalous events or objects that do not…
A New Algorithm for Applying Sequences of Affine Transformations in Quantum Circuits
Anish Giri, David Hyde, Kalman Varga
This paper introduces a robust and scalable framework for implementing nested affine transformations in quantum circuits. Utilizing Hadamard-supported conditional initialization an…
A Thermomechanical Hybrid Incompressible Material Point Method
Victoria Kala, Jingyu Chen, David Hyde +2
We present a novel hybrid incompressible flow/material point method solver for simulating the combustion of flammable solids. Our approach utilizes a sparse grid representation of…
Anvil: An integration of artificial intelligence, sampling techniques, and a combined CAD-CFD tool
Harsh Vardhan, Umesh Timalsina, Michael Sandborn +3
In this work, we introduce an open-source integrated CAD-CFD tool, Anvil, which combines FreeCAD for CAD modeling and OpenFOAM for CFD analysis, along with an AI-based optimization…
Compelling ReLU Networks to Exhibit Exponentially Many Linear Regions at Initialization and During Training
Max Milkert, David Hyde, Forrest Laine
In a neural network with ReLU activations, the number of piecewise linear regions in the output can grow exponentially with depth. However, this is highly unlikely to happen when t…