Andreas C. Damianou

Artificial Intelligence · 2011–2020

A researcher in the Science corpus: 8 papers; trusts 307 researchers and is trusted by 107 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 114 citations into it; #2,334 of 35,345 by trust here, #4,445 by citations
• Computer Vision and Pattern Recognition — 84 citations into it; #3,175 of 21,575 by trust here, #4,286 by citations
• Representation & Self-Supervised Learning — 47 citations into it
• Probabilistic & Bayesian Methods — 38 citations into it; #245 of 1,525 by trust here, #389 by citations
• Optimization & Training — 27 citations into it
• Model Architectures — 21 citations into it
• Computational Theory and Mathematics — 15 citations into it; #4,246 of 12,182 by trust here, #3,796 by citations
• Control and Systems Engineering — 13 citations into it; #3,009 of 8,257 by trust here, #5,227 by citations

Whom Andreas C. Damianou trusts overall

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

1. Neil D. Lawrence
2. Michalis K. Titsias
3. Geoffrey E. Hinton
4. Radford M. Neal
5. Yoshua Bengio
6. Diederik P. Kingma
7. Alex Krizhevsky
8. David John Cameron MacKay
9. Yann LeCun
10. Ruslan Salakhutdinov

Who trusts Andreas C. Damianou overall

1. Andrew Gordon Wilson
2. Greg Yang
3. Yarin Gal
4. Zoubin Ghahramani
5. Marc Peter Deisenroth
6. Hugh Salimbeni
7. James Hensman
8. Kyunghyun Cho
9. Neil D. Lawrence
10. Zhenwen Dai

Papers from Andreas C. Damianou's perspective

Ordered by how strongly the researchers Andreas C. Damianou trusts endorse each paper. Same corpus, a different order for every researcher.

1. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
2. ImageNet classification with deep convolutional neural networks
3. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. Gradient-based learning applied to document recognition
5. Long Short-Term Memory
6. Attention is All you Need (Neural Information Processing Systems)
7. ImageNet: A large-scale hierarchical image database
8. Learning Multiple Layers of Features from Tiny Images
9. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
10. ImageNet Large Scale Visual Recognition Challenge

Their papers

• Deep Gaussian Processes (2012) — 1,327 citations
• Variational Information Distillation for Knowledge Transfer (2019) — 763 citations
• Variational Gaussian Process Dynamical Systems (2011) — 115 citations
• Variational Auto-encoded Deep Gaussian Processes (2015) — 138 citations
• Empirical Bayes Transductive Meta-Learning with Synthetic Gradients (2020) — 140 citations
• Manifold Relevance Determination (2012) — 111 citations
• Nonlinear information fusion algorithms for data-efficient multi-fidelity modelling (2017) — 474 citations
• Transferring Knowledge across Learning Processes (2018) — 65 citations