Ronald S. Fearing
Artificial Intelligence · 1986–2019
A researcher in the Science corpus: 15 papers; trusts 91 researchers and is trusted by 62 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 90 citations into it; #4,037 of 35,345 by trust here, #5,638 by citations
- Reinforcement Learning — 86 citations into it; #487 of 2,242 by trust here, #546 by citations
- Biomedical Engineering — 51 citations into it; #578 of 10,734 by trust here, #623 by citations
- Control and Systems Engineering — 38 citations into it; #839 of 8,257 by trust here, #631 by citations
- Computer Vision and Pattern Recognition — 25 citations into it
- Mechanical Engineering — 22 citations into it; #6,481 of 8,300 by trust here, #3,532 by citations
- Aerospace Engineering — 16 citations into it; #4,377 of 6,421 by trust here, #4,945 by citations
- Computational Theory and Mathematics — 14 citations into it
Whom Ronald S. Fearing trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Sergey Levine
- Richard S. Sutton
- Chelsea Finn
- J. Urgen Schmidhuber
- Yoshua Bengio
- Marc Peter Deisenroth
- Geoffrey E. Hinton
- Pieter Abbeel
- E. Todorov
- Diederik P. Kingma
Who trusts Ronald S. Fearing overall
- Sergey Levine
- Robert J. Wood
- OpenAI
- Anusha Nagabandi
- Michael Janner
- Ignasi Clavera
- Pieter Abbeel
- David R Ha
- Abhishek Gupta
- Chelsea Finn
Papers from Ronald S. Fearing's perspective
Ordered by how strongly the researchers Ronald S. Fearing 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)
- Long Short-Term Memory
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Gradient-based learning applied to document recognition
- Attention is All you Need (Neural Information Processing Systems)
- ImageNet: A large-scale hierarchical image database
- Learning Multiple Layers of Features from Tiny Images
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
Their papers
- Neural Network Dynamics for Model-Based Deep Reinforcement Learning with Model-Free Fine-Tuning (2017) — 1,091 citations
- Learning to Adapt in Dynamic, Real-World Environments through Meta-Reinforcement Learning (2018) — 659 citations
- Nanowire active-matrix circuitry for low-voltage macroscale artificial skin. (2010) — 1,229 citations
- Optimal energy density piezoelectric bending actuators (2005) — 286 citations
- Towards a 3g crawling robot through the integration of microrobot technologies (2006) — 631 citations
- Robotic vertical jumping agility via series-elastic power modulation (2016) — 366 citations
- DASH: A dynamic 16g hexapedal robot (2009) — 299 citations
- Insect-scale fast moving and ultrarobust soft robot (2019) — 457 citations
- Learning to Adapt: Meta-Learning for Model-Based Control (2018) — 94 citations
- Bio-inspired design and dynamic maneuverability of a minimally actuated six-legged robot (2010) — 150 citations
- Microrobot Design Using Fiber Reinforced Composites (2008) — 430 citations
- Directional adhesion of gecko-inspired angled microfiber arrays (2008) — 168 citations
- Evidence for van der Waals adhesion in gecko setae (2002) — 1,871 citations
- Adhesive force of a single gecko foot-hair (2000) — 2,595 citations
- Implementing a force strategy for object re-orientation (1986)