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cs.LG2025
Neural Architecture Codesign for Fast Physics Applications
Jason Weitz, Dmitri Demler, Luke McDermott +2
We develop a pipeline to streamline neural architecture codesign for physics applications to reduce the need for ML expertise when designing models for novel tasks. Our method empl…
cs.LG2023
Neural Architecture Codesign for Fast Bragg Peak Analysis
Luke McDermott, Jason Weitz, Dmitri Demler +3
We develop an automated pipeline to streamline neural architecture codesign for fast, real-time Bragg peak analysis in high-energy diffraction microscopy. Traditional approaches, n…
cs.LG2023
Linear Mode Connectivity in Sparse Neural Networks
Luke McDermott, Daniel Cummings
With the rise in interest of sparse neural networks, we study how neural network pruning with synthetic data leads to sparse networks with unique training properties. We find that…