Michael E. Webber

Electrical and Electronic Engineering · 2008–2017

A researcher in the Science corpus: 5 papers; trusts 2 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Electrical and Electronic Engineering — 18 citations into it
• Building and Construction — 6 citations into it

Whom Michael E. Webber trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. D. Pimentel

Papers from Michael E. Webber's perspective

Ordered by how strongly the researchers Michael E. Webber trusts endorse each paper. Same corpus, a different order for every researcher.

1. Human-level control through deep reinforcement learning
2. Asynchronous Methods for Deep Reinforcement Learning
3. Deep Sparse Rectifier Neural Networks
4. Rectifier Nonlinearities Improve Neural Network Acoustic Models
5. Delving Deep into Rectifiers: Surpassing Human-Level Performance on ImageNet Classification
6. High-Dimensional Continuous Control Using Generalized Advantage Estimation
7. On rectified linear units for speech processing
8. Reinforcement learning of motor skills with policy gradients
9. Deep learning for estimating building energy consumption
10. Online Multi-Task Learning for Policy Gradient Methods

Their papers

• On-Line Building Energy Optimization Using Deep Reinforcement Learning (2017) — 552 citations
• The impacts of storing solar energy in the home to reduce reliance on the utility (2017) — 260 citations
• Evaluating the energy consumed for water use in the United States (2012) — 216 citations
• Energy-Water Nexus in Texas (2009) — 113 citations
• Cow power: the energy and emissions benefits of converting manure to biogas (2008) — 230 citations