Antonio Ortega
Artificial Intelligence · 2002–2017
A researcher in the Science corpus: 7 papers; trusts 62 researchers and is trusted by 56 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 47 citations into it; #5,204 of 35,345 by trust here, #5,252 by citations
- Computer Vision and Pattern Recognition — 47 citations into it; #6,305 of 21,575 by trust here, #13,815 by citations
- Statistical and Nonlinear Physics — 35 citations into it; #738 of 10,127 by trust here, #527 by citations
- Computational Theory and Mathematics — 32 citations into it
- Graph Learning — 23 citations into it; #190 of 693 by trust here, #167 by citations
- Computational Mechanics — 21 citations into it
- Geometry and Topology — 15 citations into it
- Applied Mathematics — 12 citations into it
Whom Antonio Ortega trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Aliaksei Sandryhaila
- Ulrike von Luxburg
- David K. Hammond
- Peyman Milanfar
- Pierre Vandergheynst
- Ronald R. Coifman
- José M. F. Moura
- Anil K. Jain
- Robert Tibshirani
- Mikhail Belkin
Who trusts Antonio Ortega overall
- William L. Hamilton
- Hilmi E. Egilmez
- Xiaowen Dong
- Aliaksei Sandryhaila
- Feng Xia
- David I. Shuman
- Siheng Chen
- Pascal Frossard
- Renjie Liao
- Tommi Kerola
Papers from Antonio Ortega's perspective
Ordered by how strongly the researchers Antonio Ortega 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
- 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)
- Learning Multiple Layers of Features from Tiny Images
- Going deeper with convolutions
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
Their papers
- The emerging field of signal processing on graphs: Extending high-dimensional data analysis to networks and other irregular domains (2012) — 4,524 citations
- Graph Signal Processing: Overview, Challenges, and Applications (2017) — 1,859 citations
- Efficient Sampling Set Selection for Bandlimited Graph Signals Using Graph Spectral Proxies (2015) — 351 citations
- Graph Learning From Data Under Laplacian and Structural Constraints (2016) — 367 citations
- P3: Toward Privacy-Preserving Photo Sharing (2013) — 152 citations
- Perfect Reconstruction Two-Channel Wavelet Filter Banks for Graph Structured Data (2011) — 411 citations
- Towards the Control of Linear Systems with Minimum Bit-Rate (2002) — 240 citations