Dimitri Palaz
Artificial Intelligence · 2013–2015
A researcher in the Science corpus: 4 papers; trusts 74 researchers and is trusted by 39 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 35 citations into it; #5,528 of 35,345 by trust here, #10,430 by citations
- Signal Processing — 26 citations into it; #842 of 7,572 by trust here, #1,351 by citations
- Speech & Audio — 24 citations into it; #560 of 1,076 by trust here, #711 by citations
- Natural Language Processing — 22 citations into it; #2,249 of 5,688 by trust here, #3,687 by citations
- Computer Vision and Pattern Recognition — 13 citations into it
- Model Architectures — 10 citations into it
- Probabilistic & Bayesian Methods — 6 citations into it
Whom Dimitri Palaz trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Yann LeCun
- L. Eon Bottou
- Ronan Collobert
- Geoffrey E. Hinton
- Abdel-rahman Mohamed
- George E. Dahl
- Yoshua Bengio
- Alex Krizhevsky
- Susannah Young
- Honglak Lee
Who trusts Dimitri Palaz overall
- Ronan Collobert
- Roni Mittelman
- Pegah Ghahremani
- Jongpil Lee
- Orestis Tsinalis
- Neil Zeghidour
- Mathew Magimai-Doss
- George Trigeorgis
- Tom Sercu
- Ron J. Weiss
Papers from Dimitri Palaz's perspective
Ordered by how strongly the researchers Dimitri Palaz 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
- Attention is All you Need (Neural Information Processing Systems)
- ImageNet: A large-scale hierarchical image database
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
- Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
Their papers
- Estimating phoneme class conditional probabilities from raw speech signal using convolutional neural networks (2013) — 209 citations
- Analysis of CNN-based speech recognition system using raw speech as input (2015) — 291 citations
- Convolutional Neural Networks-based continuous speech recognition using raw speech signal (2015) — 179 citations
- End-to-end Phoneme Sequence Recognition using Convolutional Neural Networks (2013) — 43 citations