63 citations · 71 across the 6 of their papers we have counts for
6 papers
PRECISE-AS: Personalized Reinforcement Learning for Efficient Point-of-Care Echocardiography in Aortic Stenosis Diagnosis
Armin Saadat, Nima Hashemi, Hooman Vaseli +5
Aortic stenosis (AS) is a life-threatening condition caused by a narrowing of the aortic valve, leading to impaired blood flow. Despite its high prevalence, access to echocardiogra…
Understanding the Evolution of Linear Regions in Deep Reinforcement Learning
Setareh Cohan, Nam Hee Kim, David Rolnick +1
Policies produced by deep reinforcement learning are typically characterised by their learning curves, but they remain poorly understood in many other respects. ReLU-based policies…
Style-ERD: Responsive and Coherent Online Motion Style Transfer
Tianxin Tao, Xiaohang Zhan, Zhongquan Chen +1
Motion style transfer is a common method for enriching character animation. Motion style transfer algorithms are often designed for offline settings where motions are processed in…
A Survey on Reinforcement Learning Methods in Character Animation
Ariel Kwiatkowski, Eduardo Alvarado, Vicky Kalogeiton +4
Reinforcement Learning is an area of Machine Learning focused on how agents can be trained to make sequential decisions, and achieve a particular goal within an arbitrary environme…
Learning to Correspond Dynamical Systems
Nam Hee Kim, Zhaoming Xie, Michiel van de Panne
Many dynamical systems exhibit similar structure, as often captured by hand-designed simplified models that can be used for analysis and control. We develop a method for learning t…
Iterative Reinforcement Learning Based Design of Dynamic Locomotion Skills for Cassie
Zhaoming Xie, Patrick Clary, Jeremy Dao +3
Deep reinforcement learning (DRL) is a promising approach for developing legged locomotion skills. However, the iterative design process that is inevitable in practice is poorly su…