Hagai Thomas Attias
Signal Processing · 1999–2010
A researcher in the Science corpus: 6 papers; trusts 38 researchers and is trusted by 42 researchers here, as inferred from the citation graph.
Subfields
- Signal Processing — 14 citations into it; #7,388 of 7,572 by trust here, #4,750 by citations
- Artificial Intelligence — 10 citations into it
- Probabilistic & Bayesian Methods — 9 citations into it; #311 of 1,525 by trust here, #633 by citations
- Computer Vision and Pattern Recognition — 8 citations into it; #6,994 of 21,575 by trust here, #15,162 by citations
Whom Hagai Thomas Attias trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Zoubin Ghahramani
- Geoffrey E. Hinton
- David M. Blei
- Michael I. Jordan
- Radford M. Neal
- Lawrence K. Saul
- Yariv Ephraim
- Matthew J. Beal
- Yoshua Bengio
- Daphne Koller
Who trusts Hagai Thomas Attias overall
- David M. Blei
- Sergey Levine
- Michael I. Jordan
- Zoubin Ghahramani
- Chong Wang
- Marc Toussaint
- Matthew J. Beal
- E. Todorov
- David Paul Wipf
- Paul David McNicholas
Papers from Hagai Thomas Attias's perspective
Ordered by how strongly the researchers Hagai Thomas Attias trusts endorse each paper. Same corpus, a different order for every researcher.
- ImageNet classification with deep convolutional neural networks
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Long Short-Term Memory
- Gradient-based learning applied to document recognition
- ImageNet: A large-scale hierarchical image database
- Attention is All you Need (Neural Information Processing Systems)
- Learning Multiple Layers of Features from Tiny Images
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
Their papers
- Topic regression multi-modal Latent Dirichlet Allocation for image annotation (2010) — 206 citations
- Blind Source Separation Exploiting Higher-Order Frequency Dependencies (2007) — 468 citations
- A Probabilistic Algorithm Integrating Source Localization and Noise Suppression of MEG and EEG data (2006) — 70 citations
- Planning by Probabilistic Inference (2003) — 308 citations
- Speech Denoising and Dereverberation Using Probabilistic Models (2000) — 110 citations
- A Variational Bayesian Framework for Graphical Models (1999)