Learning to drive by imitation: An overview of deep behavior cloning methods
AO Ly, M Akhloufi - IEEE Transactions on Intelligent Vehicles, 2020 - ieeexplore.ieee.org
There is currently a huge interest around autonomous vehicles from both industry and
academia. This is mainly due to recent advances in machine learning and deep learning …
academia. This is mainly due to recent advances in machine learning and deep learning …
Enhancing scientific discoveries in molecular biology with deep generative models
Generative models provide a well‐established statistical framework for evaluating
uncertainty and deriving conclusions from large data sets especially in the presence of …
uncertainty and deriving conclusions from large data sets especially in the presence of …
Exploring the limitations of behavior cloning for autonomous driving
Driving requires reacting to a wide variety of complex environment conditions and agent
behaviors. Explicitly modeling each possible scenario is unrealistic. In contrast, imitation …
behaviors. Explicitly modeling each possible scenario is unrealistic. In contrast, imitation …
Deep federated learning for autonomous driving
Autonomous driving is an active research topic in both academia and industry. However,
most of the existing solutions focus on improving the accuracy by training learnable models …
most of the existing solutions focus on improving the accuracy by training learnable models …
Learning robust control policies for end-to-end autonomous driving from data-driven simulation
In this work, we present a data-driven simulation and training engine capable of learning
end-to-end autonomous vehicle control policies using only sparse rewards. By leveraging …
end-to-end autonomous vehicle control policies using only sparse rewards. By leveraging …
Multimodal end-to-end autonomous driving
A crucial component of an autonomous vehicle (AV) is the artificial intelligence (AI) is able to
drive towards a desired destination. Today, there are different paradigms addressing the …
drive towards a desired destination. Today, there are different paradigms addressing the …
Uncovering and mitigating algorithmic bias through learned latent structure
Recent research has highlighted the vulnerabilities of modern machine learning based
systems to bias, especially towards segments of society that are under-represented in …
systems to bias, especially towards segments of society that are under-represented in …
Vista 2.0: An open, data-driven simulator for multimodal sensing and policy learning for autonomous vehicles
Simulation has the potential to transform the development of robust algorithms for mobile
agents deployed in safety-critical scenarios. However, the poor photorealism and lack of …
agents deployed in safety-critical scenarios. However, the poor photorealism and lack of …
Variational end-to-end navigation and localization
Deep learning has revolutionized the ability to learn “end-to-end” autonomous vehicle
control directly from raw sensory data. While there have been recent extensions to handle …
control directly from raw sensory data. While there have been recent extensions to handle …
Driving in dense traffic with model-free reinforcement learning
Traditional planning and control methods could fail to find a feasible trajectory for an
autonomous vehicle to execute amongst dense traffic on roads. This is because the obstacle …
autonomous vehicle to execute amongst dense traffic on roads. This is because the obstacle …