152 citations · 238 across the 8 of their papers we have counts for
4 papers · 1 filter
Scalable Deep Generative Modeling for Sparse Graphs
Hanjun Dai, Azade Nazi, Yujia Li +2
Learning graph generative models is a challenging task for deep learning and has wide applicability to a range of domains like chemistry, biology and social science. However curren…
Chip Placement with Deep Reinforcement Learning
Azalia Mirhoseini, Anna Goldie, Mustafa Yazgan +19
In this work, we present a learning-based approach to chip placement, one of the most complex and time-consuming stages of the chip design process. Unlike prior methods, our approa…
Generalized Clustering by Learning to Optimize Expected Normalized Cuts
Azade Nazi, Will Hang, Anna Goldie +2
We introduce a novel end-to-end approach for learning to cluster in the absence of labeled examples. Our clustering objective is based on optimizing normalized cuts, a criterion wh…
GAP: Generalizable Approximate Graph Partitioning Framework
Azade Nazi, Will Hang, Anna Goldie +2
Graph partitioning is the problem of dividing the nodes of a graph into balanced partitions while minimizing the edge cut across the partitions. Due to its combinatorial nature, ma…