Mauricio A Álvarez

Artificial Intelligence · 2008–2019

A researcher in the Science corpus: 7 papers; trusts 49 researchers and is trusted by 40 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 58 citations into it; #5,031 of 35,345 by trust here, #9,641 by citations
• Probabilistic & Bayesian Methods — 38 citations into it; #543 of 1,525 by trust here, #895 by citations
• Environmental Engineering — 29 citations into it
• Computational Theory and Mathematics — 19 citations into it
• Statistical Learning Theory — 19 citations into it; #426 of 1,038 by trust here, #424 by citations
• Statistics and Probability — 19 citations into it
• Economics and Econometrics — 14 citations into it
• Representation & Self-Supervised Learning — 12 citations into it

Whom Mauricio A Álvarez trusts overall

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

1. Neil D. Lawrence
2. D. Higdon
3. Phillip Boyle
4. Matthias W. Seeger
5. Edwin V. Bonilla
6. Christopher K. I. Williams
7. Edward Snelson
8. Joaquin Quiñonero Candela
9. Carl E. Rasmussen
10. Montserrat Fuentes

Who trusts Mauricio A Álvarez overall

1. Haitao Liu
2. Neil D. Lawrence
3. Yew-Soon Ong
4. Lorenzo Rosasco
5. Ahmed M. Alaa
6. Jianfei Cai
7. Michalis K. Titsias
8. Pablo Moreno-Muñoz
9. Andrew Gordon Wilson
10. James Hensman

Papers from Mauricio A Álvarez's perspective

Ordered by how strongly the researchers Mauricio A Álvarez 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. Learning Multiple Layers of Features from Tiny Images
5. Gradient-based learning applied to document recognition
6. Long Short-Term Memory
7. Attention is All you Need (Neural Information Processing Systems)
8. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
9. ImageNet: A large-scale hierarchical image database
10. Auto-Encoding Variational Bayes (International Conference on Learning Representations)

Their papers

• Kernels for Vector-Valued Functions: a Review (2011) — 1,083 citations
• Computationally Efficient Convolved Multiple Output Gaussian Processes (2011) — 346 citations
• Continual Multi-task Gaussian Processes (2019) — 14 citations
• Convolved Gaussian process priors for multivariate regression with applications to dynamical systems (2011) — 10 citations
• Efficient Multioutput Gaussian Processes through Variational Inducing Kernels (2010) — 142 citations
• Latent Force Models (2009) — 222 citations
• Sparse Convolved Gaussian Processes for Multi-output Regression (2008) — 235 citations