6 papers
Interpretability and Generalization Bounds for Learning Spatial Physics
Alejandro Francisco Queiruga, Theo Gutman-Solo, Shuai Jiang
While there are many applications of ML to scientific problems that look promising, visuals can be deceiving. Using numerical analysis techniques, we rigorously quantify the accura…
OpenVTON-Bench: A Large-Scale High-Resolution Benchmark for Controllable Virtual Try-On Evaluation
Jin Li, Tao Chen, Kai Wen +5
Recent advances in diffusion models have significantly elevated the visual fidelity of Virtual Try-On (VTON) systems, yet reliable evaluation remains a persistent bottleneck. Tradi…
On the Convergence Behavior of Preconditioned Gradient Descent Toward the Rich Learning Regime
Shuai Jiang, Alexey Voronin, Eric Cyr +1
Spectral bias, the tendency of neural networks to learn low frequencies first, can be both a blessing and a curse. While it enhances the generalization capabilities by suppressing…
Layer-Parallel Training for Transformers
Shuai Jiang, Marc Salvadó-Benasco, Eric C. Cyr +3
We present a new training methodology for transformers using a multilevel, layer-parallel approach. Through a neural ODE formulation of transformers, our application of a multileve…
Automated Neural Architecture Design for Industrial Defect Detection
Yuxi Liu, Yunfeng Ma, Yi Tang +3
Industrial surface defect detection (SDD) is critical for ensuring product quality and manufacturing reliability. Due to the diverse shapes and sizes of surface defects, SDD faces…
Resilient Multimodal Industrial Surface Defect Detection with Uncertain Sensors Availability
Shuai Jiang, Yunfeng Ma, Jingyu Zhou +3
Multimodal industrial surface defect detection (MISDD) aims to identify and locate defect in industrial products by fusing RGB and 3D modalities. This article focuses on modality-m…