172 citations · 195 across the 19 of their papers we have counts for
4 papers · 1 filter
Haldane Bundles: A Dataset for Learning to Predict the Chern Number of Line Bundles on the Torus
Cody Tipton, Elizabeth Coda, Davis Brown +5
Characteristic classes, which are abstract topological invariants associated with vector bundles, have become an important notion in modern physics with surprising real-world conse…
ICML 2023 Topological Deep Learning Challenge : Design and Results
Mathilde Papillon, Mustafa Hajij, Helen Jenne +53
This paper presents the computational challenge on topological deep learning that was hosted within the ICML 2023 Workshop on Topology and Geometry in Machine Learning. The competi…
Reproducing Kernel Hilbert Space Pruning for Sparse Hyperspectral Abundance Prediction
Michael G. Rawson, Timothy Doster
Hyperspectral measurements from long range sensors can give a detailed picture of the items, materials, and chemicals in a scene but analysis can be difficult, slow, and expensive…
Parameters, Properties, and Process: Conditional Neural Generation of Realistic SEM Imagery Towards ML-assisted Advanced Manufacturing
Scott Howland, Lara Kassab, Keerti Kappagantula +2
The research and development cycle of advanced manufacturing processes traditionally requires a large investment of time and resources. Experiments can be expensive and are hence c…