127 citations · 220 across the 16 of their papers we have counts for
16 papers
Representing Long-Range Context for Graph Neural Networks with Global Attention
Zhanghao Wu, Paras Jain, Matthew A. Wright +3
Graph neural networks are powerful architectures for structured datasets. However, current methods struggle to represent long-range dependencies. Scaling the depth or width of GNNs…
Transformers are Deep Infinite-Dimensional Non-Mercer Binary Kernel Machines
Matthew A. Wright, Joseph E. Gonzalez
Despite their ubiquity in core AI fields like natural language processing, the mechanics of deep attention-based neural networks like the Transformer model are not fully understood…
Contingencies from Observations: Tractable Contingency Planning with Learned Behavior Models
Nicholas Rhinehart, Jeff He, Charles Packer +4
Humans have a remarkable ability to make decisions by accurately reasoning about future events, including the future behaviors and states of mind of other agents. Consider driving…
Pylot: A Modular Platform for Exploring Latency-Accuracy Tradeoffs in Autonomous Vehicles
Ionel Gog, Sukrit Kalra, Peter Schafhalter +3
We present Pylot, a platform for autonomous vehicle (AV) research and development, built with the goal to allow researchers to study the effects of the latency and accuracy of thei…
Macroscopic Modeling, Calibration, and Simulation of Managed Lane-Freeway Networks, Part II: Network-scale Calibration and Case Studies
Matthew A. Wright, Roberto Horowitz, Alex A. Kurzhanskiy
In Part I of this paper series, several macroscopic traffic model elements for mathematically describing freeway networks equipped with managed lane facilities were proposed. These…
Attentional Policies for Cross-Context Multi-Agent Reinforcement Learning
Matthew A. Wright, Roberto Horowitz
Many potential applications of reinforcement learning in the real world involve interacting with other agents whose numbers vary over time. We propose new neural policy architectur…