20 citations · 29 across the 6 of their papers we have counts for
7 papers
AutoBrep: Autoregressive B-Rep Generation with Unified Topology and Geometry
Xiang Xu, Pradeep Kumar Jayaraman, Joseph G. Lambourne +3
The boundary representation (B-Rep) is the standard data structure used in Computer-Aided Design (CAD) for defining solid models. Despite recent progress, directly generating B-Rep…
What's in a Name? Evaluating Assembly-Part Semantic Knowledge in Language Models through User-Provided Names in CAD Files
Peter Meltzer, Joseph G. Lambourne, Daniele Grandi
Semantic knowledge of part-part and part-whole relationships in assemblies is useful for a variety of tasks from searching design repositories to the construction of engineering kn…
UVStyle-Net: Unsupervised Few-shot Learning of 3D Style Similarity Measure for B-Reps
Peter Meltzer, Hooman Shayani, Amir Khasahmadi +3
Boundary Representations (B-Reps) are the industry standard in 3D Computer Aided Design/Manufacturing (CAD/CAM) and industrial design due to their fidelity in representing stylisti…
BRepNet: A topological message passing system for solid models
Joseph G. Lambourne, Karl D. D. Willis, Pradeep Kumar Jayaraman +3
Boundary representation (B-rep) models are the standard way 3D shapes are described in Computer-Aided Design (CAD) applications. They combine lightweight parametric curves and surf…
PiNet: Attention Pooling for Graph Classification
Peter Meltzer, Marcelo Daniel Gutierrez Mallea, Peter J. Bentley
We propose PiNet, a generalised differentiable attention-based pooling mechanism for utilising graph convolution operations for graph level classification. We demonstrate high samp…
PiNet: A Permutation Invariant Graph Neural Network for Graph Classification
Peter Meltzer, Marcelo Daniel Gutierrez Mallea, Peter J. Bentley
We propose an end-to-end deep learning learning model for graph classification and representation learning that is invariant to permutation of the nodes of the input graphs. We add…