Joseph P. Turian
Artificial Intelligence · 2003–2020
A researcher in the Science corpus: 5 papers; trusts 51 researchers and is trusted by 242 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 143 citations into it; #14,147 of 35,345 by trust here, #3,878 by citations
- Natural Language Processing — 132 citations into it; #354 of 5,688 by trust here, #655 by citations
- Computer Vision and Pattern Recognition — 88 citations into it
- Representation & Self-Supervised Learning — 32 citations into it; #231 of 3,145 by trust here, #445 by citations
- Model Architectures — 17 citations into it
- Large Language Models — 16 citations into it
- Philosophy — 12 citations into it
Whom Joseph P. Turian trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Magnus Sahlgren
- Yoshua Bengio
- Geoffrey E. Hinton
- Ronan Collobert
- Andriy Mnih
- Percy Liang
- Jason Aaron Edward Weston
- Diederik P. Kingma
- Yann LeCun
- Alex Krizhevsky
Who trusts Joseph P. Turian overall
- Richard Socher
- Thien Huu Nguyen
- Mohit Bansal
- Christopher D. Manning
- Yoshua Bengio
- Quoc V. Le
- Chris Dyer
- Tomas Mikolov
- Xipeng Qiu
- Wenpeng Yin
Papers from Joseph P. Turian's perspective
Ordered by how strongly the researchers Joseph P. Turian 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)
- Attention is All you Need (Neural Information Processing Systems)
- 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
- BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
- Going deeper with convolutions
- Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
Their papers
- Experience Grounds Language (2020) — 440 citations
- Theano: A CPU and GPU Math Compiler in Python (2010) — 862 citations
- Evaluation of machine translation and its evaluation (2003) — 335 citations
- Theano: A Python framework for fast computation of mathematical expressions (2016) — 2,380 citations
- Word Representations: A Simple and General Method for Semi-Supervised Learning (2010) — 2,346 citations