The question of how methods from the field of artificial intelligence can help improve the
conventional frameworks for topology optimisation has received increasing attention over …

In additive manufacturing (AM), intelligent technologies are proving to be a powerful tool for
facilitating economic, efficient, and effective decision-making within the product and service …

We introduce ABC-Dataset, a collection of one million Computer-Aided Design (CAD)
models for research of geometric deep learning methods and applications. Each model is a …

An e-graph efficiently represents a congruence relation over many expressions. Although
they were originally developed in the late 1970s for use in automated theorem provers, a …

Reverse engineering in the realm of Computer-Aided Design (CAD) has been a
longstanding aspiration though not yet entirely realized. Its primary aim is to uncover the …

CAD modeling, despite being the industry-standard, remains restricted to usage by skilled
practitioners due to two key barriers. First, the user must be able to mentally parse a final …

Fitting geometric primitives to 3D point cloud data bridges a gap between low-level digitized
3D data and high-level structural information on the underlying 3D shapes. As such, it …

Parametric computer-aided design (CAD) is a standard paradigm used to design
manufactured objects, where a 3D shape is represented as a program supported by the …

We view the reconstruction of CAD models in the boundary representation (B-Rep) as the
detection of geometric primitives of different orders, ie, vertices, edges and surface patches …

Reverse engineering CAD models from raw geometry is a classic but strenuous research
problem. Previous learning-based methods rely heavily on labels due to the supervised …