Safe learning in robotics: From learning-based control to safe reinforcement learning
The last half decade has seen a steep rise in the number of contributions on safe learning
methods for real-world robotic deployments from both the control and reinforcement learning …
methods for real-world robotic deployments from both the control and reinforcement learning …
Combustion machine learning: Principles, progress and prospects
Progress in combustion science and engineering has led to the generation of large amounts
of data from large-scale simulations, high-resolution experiments, and sensors. This corpus …
of data from large-scale simulations, high-resolution experiments, and sensors. This corpus …
Synaptic plasticity forms and functions
Synaptic plasticity, the activity-dependent change in neuronal connection strength, has long
been considered an important component of learning and memory. Computational and …
been considered an important component of learning and memory. Computational and …
Machine learning methods that economists should know about
We discuss the relevance of the recent machine learning (ML) literature for economics and
econometrics. First we discuss the differences in goals, methods, and settings between the …
econometrics. First we discuss the differences in goals, methods, and settings between the …
A tour of reinforcement learning: The view from continuous control
B Recht - Annual Review of Control, Robotics, and Autonomous …, 2019 - annualreviews.org
This article surveys reinforcement learning from the perspective of optimization and control,
with a focus on continuous control applications. It reviews the general formulation …
with a focus on continuous control applications. It reviews the general formulation …
Physical principles of brain–computer interfaces and their applications for rehabilitation, robotics and control of human brain states
Brain–computer interfaces (BCIs) development is closely related to physics. In this paper, we
review the physical principles of BCIs, and underlying novel approaches for registration …
review the physical principles of BCIs, and underlying novel approaches for registration …
Precision medicine
Precision medicine seeks to maximize the quality of health care by individualizing the health-
care process to the uniquely evolving health status of each patient. This endeavor spans a …
care process to the uniquely evolving health status of each patient. This endeavor spans a …
Machine learning for fluid mechanics
The field of fluid mechanics is rapidly advancing, driven by unprecedented volumes of data
from experiments, field measurements, and large-scale simulations at multiple …
from experiments, field measurements, and large-scale simulations at multiple …
Imitating driver behavior with generative adversarial networks
The ability to accurately predict and simulate human driving behavior is critical for the
development of intelligent transportation systems. Traditional modeling methods have …
development of intelligent transportation systems. Traditional modeling methods have …
Q-learning: Theory and applications
J Clifton, E Laber - Annual Review of Statistics and Its …, 2020 - annualreviews.org
Q-learning, originally an incremental algorithm for estimating an optimal decision strategy in
an infinite-horizon decision problem, now refers to a general class of reinforcement learning …
an infinite-horizon decision problem, now refers to a general class of reinforcement learning …