Semi-supervised deep learning for high-dimensional uncertainty quantification

no code implementations • 1 Jun 2020 • Zequn Wang, Mingyang Li

Conventional uncertainty quantification methods usually lacks the capability of dealing with high-dimensional problems due to the curse of dimensionality.

Dimensionality Reduction Uncertainty Quantification +1

Proximal Reliability Optimization for Reinforcement Learning

no code implementations • 3 Jun 2019 • Narendra Patwardhan, Zequn Wang

Despite the numerous advances, reinforcement learning remains away from widespread acceptance for autonomous controller design as compared to classical methods due to lack of ability to effectively tackle the reality gap.

reinforcement-learning Reinforcement Learning (RL)

Reinforcement Learning for Robotics and Control with Active Uncertainty Reduction

no code implementations • 15 May 2019 • Narendra Patwardhan, Zequn Wang

Model-based methods such as PILCO or BlackDrops, while data-efficient, provide solutions with limited robustness and complexity.

Management OpenAI Gym +3