Michael F. P. O'Boyle
Artificial Intelligence · 2006–2020
A researcher in the Science corpus: 3 papers; trusts 100 researchers and is trusted by 0 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 63 citations into it
- Computer Vision and Pattern Recognition — 57 citations into it
- Efficiency & Compression — 24 citations into it
- Model Architectures — 16 citations into it
- Representation & Self-Supervised Learning — 15 citations into it
- Optimization & Training — 11 citations into it
- Probabilistic & Bayesian Methods — 7 citations into it
Whom Michael F. P. O'Boyle trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Geoffrey E. Hinton
- Alex Krizhevsky
- Yoshua Bengio
- Kaiming He
- Ruslan Salakhutdinov
- Yann LeCun
- Diederik P. Kingma
- J. Urgen Schmidhuber
- Chelsea Finn
- Sergey Ioffe
Papers from Michael F. P. O'Boyle's perspective
Ordered by how strongly the researchers Michael F. P. O'Boyle trusts endorse each paper. Same corpus, a different order for every researcher.
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- ImageNet classification with deep convolutional neural networks
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Gradient-based learning applied to document recognition
- ImageNet: A large-scale hierarchical image database
- Attention is All you Need (Neural Information Processing Systems)
- Long Short-Term Memory
- Learning Multiple Layers of Features from Tiny Images
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- ImageNet Large Scale Visual Recognition Challenge
Their papers
- Using machine learning to focus iterative optimization (2006) — 500 citations
- Bayesian Meta-Learning for the Few-Shot Setting via Deep Kernels (2020) — 163 citations
- Pruning neural networks: is it time to nip it in the bud? (2018) — 31 citations