Pavel P. Kuksa
Natural Language Processing · 2011–2023
A researcher in the Science corpus: 3 papers; trusts 33 researchers and is trusted by 467 researchers here, as inferred from the citation graph.
Subfields
- Natural Language Processing — 42 citations into it; #378 of 5,688 by trust here, #275 by citations
- Artificial Intelligence — 41 citations into it; #818 of 35,345 by trust here, #1,081 by citations
- Information Extraction — 23 citations into it
- Representation & Self-Supervised Learning — 13 citations into it
- Optimization & Training — 10 citations into it
- Probabilistic & Bayesian Methods — 10 citations into it
- Model Architectures — 9 citations into it
- Computational Linguistics & Semantics — 8 citations into it
Whom Pavel P. Kuksa trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Geoffrey E. Hinton
- Yoshua Bengio
- Yann LeCun
- Marc'Aurelio Ranzato
- L. Eon Bottou
- Alex Krizhevsky
- Radford M. Neal
- Diederik P. Kingma
- Simon Osindero
- Ilya Sutskever
Who trusts Pavel P. Kuksa overall
- Yoshua Bengio
- Mohit Bansal
- Zhe Gan
- Jianfeng Gao
- Xipeng Qiu
- Li Deng
- Kyunghyun Cho
- Yann LeCun
- Yoav Goldberg
- Christopher D. Manning
Papers from Pavel P. Kuksa's perspective
Ordered by how strongly the researchers Pavel P. Kuksa 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)
- Gradient-based learning applied to document recognition
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Long Short-Term Memory
- Attention is All you Need (Neural Information Processing Systems)
- ImageNet: A large-scale hierarchical image database
- 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
- Natural Language Processing (Almost) from Scratch (2011) — 7,931 citations
- High-order neural networks and kernel methods for peptide-MHC binding prediction (2015) — 35 citations
- Multi-ancestry genome-wide meta-analysis of 56,241 individuals identifies LRRC4C, LHX5-AS1 and nominates ancestry-specific loci PTPRK, GRB14, and KIAA0825 as novel risk loci for Alzheimer disease: the Alzheimer Disease Genetics Consortium (2023) — 1,168 citations