89 citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- Autodesk (Canada)CA5 papers
- University of TorontoCA4 papers
- Carnegie Mellon UniversityUS3 papers
- Massachusetts Institute of TechnologyUS3 papers
- Amirkabir University of TechnologyIR2 papers
- Autodesk (United Kingdom)GB2 papers
- City University of New YorkUS2 papers
- Google (United States)US2 papers
- Moscow Institute of Thermal TechnologyRU2 papers
- New York UniversityUS2 papers
- Pennsylvania State UniversityUS2 papers
- Simon Fraser UniversityCA2 papers
7 papers · 1 filter
Reliability of Probabilistic Emulation of Physical Systems
Sam F. Greenbury, Radka Jersakova, Paolo Conti +5
Two dominant approaches have emerged for generating probabilistic forecasts of physical systems: generative models, such as diffusion or flow matching; and ensembles of determinist…
Representation Learning for Sequential Volumetric Design Tasks
Md Ferdous Alam, Yi Wang, Chin-Yi Cheng +1
Volumetric design, also called massing design, is the first and critical step in professional building design which is sequential in nature. As the volumetric design process requir…
Structural Design Recommendations in the Early Design Phase using Machine Learning
Spyridon Ampanavos, Mehdi Nourbakhsh, Chin-Yi Cheng
Structural engineering knowledge can be of significant importance to the architectural design team during the early design phase. However, architects and engineers do not typically…
Robust Representation Learning via Perceptual Similarity Metrics
Saeid Asgari Taghanaki, Kristy Choi, Amir Khasahmadi +1
A fundamental challenge in artificial intelligence is learning useful representations of data that yield good performance on a downstream task, without overfitting to spurious inpu…
Fusion 360 Gallery: A Dataset and Environment for Programmatic CAD Construction from Human Design Sequences
Karl D. D. Willis, Yewen Pu, Jieliang Luo +5
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 CAD software. Despi…
Learning to simulate and design for structural engineering
Kai-Hung Chang, Chin-Yi Cheng
The structural design process for buildings is time-consuming and laborious. To automate this process, structural engineers combine optimization methods with simulation tools to fi…
Memory-Based Graph Networks
Amir Hosein Khasahmadi, Kaveh Hassani, Parsa Moradi +2
Graph neural networks (GNNs) are a class of deep models that operate on data with arbitrary topology represented as graphs. We introduce an efficient memory layer for GNNs that can…