Improving the generalizability and robustness of large-scale traffic signal control

no code implementations • 2 Jun 2023 • Tianyu Shi, Francois-Xavier Devailly, Denis Larocque, Laurent Charlin

Building upon the state-of-the-art previous model which uses a decentralized approach for large-scale traffic signal control with graph convolutional networks (GCNs), we first learn models using a distributional reinforcement learning (DisRL) approach.

Distributional Reinforcement Learning Multi-agent Reinforcement Learning +2

RCC-GAN: Regularized Compound Conditional GAN for Large-Scale Tabular Data Synthesis

no code implementations • 24 May 2022 • Mohammad Esmaeilpour, Nourhene Chaalia, Adel Abusitta, Francois-Xavier Devailly, Wissem Maazoun, Patrick Cardinal

We refer to this noble definition as compound conditional vector and employ it for training the generator network.

Benchmarking Generative Adversarial Network

Bi-Discriminator Class-Conditional Tabular GAN

no code implementations • 12 Nov 2021 • Mohammad Esmaeilpour, Nourhene Chaalia, Adel Abusitta, Francois-Xavier Devailly, Wissem Maazoun, Patrick Cardinal

This paper introduces a bi-discriminator GAN for synthesizing tabular datasets containing continuous, binary, and discrete columns.

Benchmarking