Brenna D. Argall
Cognitive Neuroscience · 2004–2019
A researcher in the Science corpus: 8 papers; trusts 34 researchers and is trusted by 81 researchers here, as inferred from the citation graph.
Subfields
- Cognitive Neuroscience — 49 citations into it; #8,103 of 10,852 by trust here, #3,487 by citations
- Artificial Intelligence — 37 citations into it; #3,369 of 35,345 by trust here, #2,680 by citations
- Control and Systems Engineering — 35 citations into it; #319 of 8,257 by trust here, #74 by citations
- Biomedical Engineering — 33 citations into it; #2,111 of 10,734 by trust here, #7,279 by citations
- Social Psychology — 27 citations into it
- Reinforcement Learning — 25 citations into it; #312 of 2,242 by trust here, #260 by citations
- Cellular and Molecular Neuroscience — 14 citations into it
- Robotics & Control — 12 citations into it; #172 of 609 by trust here, #564 by citations
Whom Brenna D. Argall trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Kevin B. Englehart
- B. Hudgins
- Tom Carlson
- Christopher G. Atkeson
- Aude Gemma Billard
- Philip A. Parker
- Stefan Schaal
- Pieter Abbeel
- Yonghong Huang
- J. Bagnell
Who trusts Brenna D. Argall overall
- Anca Dragan
- Sergey Levine
- Dylan P. Losey
- Siddharth Karamcheti
- J. Urgen Schmidhuber
- Scott Niekum
- Stefanos Nikolaidis
- Pieter Abbeel
- Peter Stone
- Stéphane Ross
Papers from Brenna D. Argall's perspective
Ordered by how strongly the researchers Brenna D. Argall trusts endorse each paper. Same corpus, a different order for every researcher.
- ImageNet classification with deep convolutional neural networks
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Gradient-based learning applied to document recognition
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Long Short-Term Memory
- ImageNet: A large-scale hierarchical image database
- Attention is All you Need (Neural Information Processing Systems)
- GENERATIVE ADVERSARIAL NETS
- Reinforcement Learning: An Introduction
- Learning Multiple Layers of Features from Tiny Images
Their papers
- A survey of robot learning from demonstration (2009) — 4,034 citations
- Real-time natural language corrections for assistive robotic manipulators (2017) — 33 citations
- Learning robot motion control with demonstration and advice-operators (2008) — 88 citations
- A survey of Tactile Human-Robot Interactions (2010) — 329 citations
- Autonomy in Rehabilitation Robotics: An Intersection (2018) — 62 citations
- Probabilistic Human Intent Recognition for Shared Autonomy in Assistive Robotics (2019) — 137 citations
- Human-in-the-Loop Optimization of Shared Autonomy in Assistive Robotics (2017) — 177 citations
- Integration of auditory and visual information about objects in superior temporal sulcus. (2004) — 771 citations