Paul D. Gader
Media Technology · 2001–2014
A researcher in the Science corpus: 5 papers; trusts 47 researchers and is trusted by 11 researchers here, as inferred from the citation graph.
Subfields
- Media Technology — 72 citations into it; #2,530 of 3,621 by trust here, #897 by citations
- Computational Mechanics — 32 citations into it
- Analytical Chemistry — 29 citations into it; #833 of 1,254 by trust here, #259 by citations
- Atmospheric Science — 29 citations into it
- Artificial Intelligence — 24 citations into it; #15,686 of 35,345 by trust here, #10,942 by citations
- Computer Vision and Pattern Recognition — 23 citations into it
- Ecology — 23 citations into it
- Biomedical Engineering — 13 citations into it
Whom Paul D. Gader trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- José M. Bioucas-Dias
- David John Cameron MacKay
- Marian-Daniel Iordache
- Michael I. Jordan
- Robert A. Jacobs
- Geoffrey E. Hinton
- Antonio J. Plaza
- Volker Tresp
- Michael I. Jordanzoubin
- Lijuan Cao
Who trusts Paul D. Gader overall
Papers from Paul D. Gader's perspective
Ordered by how strongly the researchers Paul D. Gader 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
- Maximum likelihood from incomplete data via the EM - algorithm plus discussions on the paper
- Long Short-Term Memory
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- ImageNet: A large-scale hierarchical image database
- Attention is All you Need (Neural Information Processing Systems)
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
Their papers
- Twenty Years of Mixture of Experts (2012) — 684 citations
- A Review of Nonlinear Hyperspectral Unmixing Methods (2014) — 539 citations
- A Signal Processing Perspective on Hyperspectral Unmixing: Insights from Remote Sensing (2014) — 419 citations
- Hyperspectral Unmixing Overview: Geometrical, Statistical, and Sparse Regression-Based Approaches (2012) — 2,769 citations
- Landmine detection with ground penetrating radar using hidden Markov models (2001) — 323 citations