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Found 5 papers, 1 papers with code
Component Segmentation of Engineering Drawings Using Graph Convolutional Networks
We test our framework in the context of semantic segmentation of text, dimension and, contour components in engineering drawings.
Attention Routing: track-assignment detailed routing using attention-based reinforcement learning
We also discover a similarity between the attention router and the baseline genetic router in terms of positive correlations in cost and routing patterns, which demonstrate the attention router's ability to be utilized not only as a detailed router but also as a predictor for routability and congestion.
A Deep Reinforcement Learning Approach for Global Routing
At the heart of the proposed method is deep reinforcement learning that enables an agent to produce an optimal policy for routing based on the variety of problems it is presented with leveraging the conjoint optimization mechanism of deep reinforcement learning.
3D Shape Synthesis for Conceptual Design and Optimization Using Variational Autoencoders
We propose a data-driven 3D shape design method that can learn a generative model from a corpus of existing designs, and use this model to produce a wide range of new designs.
Data-driven Upsampling of Point Clouds
High quality upsampling of sparse 3D point clouds is critically useful for a wide range of geometric operations such as reconstruction, rendering, meshing, and analysis.
