Jose A. Costa
Computer Networks and Communications · 2004–2006
A researcher in the Science corpus: 2 papers; trusts 18 researchers and is trusted by 16 researchers here, as inferred from the citation graph.
Subfields
- Computer Networks and Communications — 12 citations into it; #4,515 of 9,886 by trust here, #7,492 by citations
- Electrical and Electronic Engineering — 11 citations into it; #5,879 of 16,539 by trust here, #13,553 by citations
- Representation & Self-Supervised Learning — 8 citations into it
- Computer Vision and Pattern Recognition — 6 citations into it; #7,331 of 21,575 by trust here, #16,367 by citations
- Artificial Intelligence — 5 citations into it
Whom Jose A. Costa trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Balázs Kégl
- Iroon Polytechniou
- Josh Tenenbaum
- Vin de Silva
- Sam T. Roweis
- Mikhail Belkin
- David L. Donoho
- Anil K. Jain
- Francesco Camastra
- Kenneth L. Lange
Who trusts Jose A. Costa overall
- Kenneth L. Clarkson
- Zheng Yang
- Francesco Camastra
- Chenshu Wu
- Richard Baraniuk
- Elizaveta Levina
- Peter J. Bickel
- Anil Jayanti Aswani
- Usman A. Khan
- Hoshin V. Gupta
Papers from Jose A. Costa's perspective
Ordered by how strongly the researchers Jose A. Costa trusts endorse each paper. Same corpus, a different order for every researcher.
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Gradient-based learning applied to document recognition
- ImageNet classification with deep convolutional neural networks
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Long Short-Term Memory
- A global geometric framework for nonlinear dimensionality reduction.
- ImageNet: A large-scale hierarchical image database
- Attention is All you Need (Neural Information Processing Systems)
- Nonlinear dimensionality reduction by locally linear embedding.
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
Their papers
- Distributed weighted-multidimensional scaling for node localization in sensor networks (2006) — 590 citations
- Geodesic entropic graphs for dimension and entropy estimation in manifold learning (2004) — 306 citations