Tim Weninger

Artificial Intelligence · 2016–2017

A researcher in the Science corpus: 2 papers; trusts 83 researchers and is trusted by 26 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 41 citations into it; #7,759 of 35,345 by trust here, #17,110 by citations
• Natural Language Processing — 13 citations into it
• Graph Learning — 12 citations into it
• Representation & Self-Supervised Learning — 10 citations into it
• Management Science and Operations Research — 8 citations into it; #3,656 of 11,946 by trust here, #6,314 by citations
• Computer Vision and Pattern Recognition — 7 citations into it
• Statistical and Nonlinear Physics — 7 citations into it
• Information Systems — 6 citations into it

Whom Tim Weninger trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. Antoine Bordes
2. Richard Socher
3. Yankai Lin
4. Diederik P. Kingma
5. Yoshua Bengio
6. Geoffrey E. Hinton
7. Maximilian Nickel
8. Ilya Sutskever
9. Zhiyuan Liu
10. Christopher D. Manning

Who trusts Tim Weninger overall

1. Sahisnu Mazumder
2. Baoxu Shi
3. Lingbing Guo
4. Hongyun Cai
5. Zhe Chen
6. Ciyuan Peng
7. Dai Quoc Nguyen
8. Nianzu Ma
9. K. Liang
10. Bo Wang

Papers from Tim Weninger's perspective

Ordered by how strongly the researchers Tim Weninger trusts endorse each paper. Same corpus, a different order for every researcher.

1. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
2. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
3. ImageNet classification with deep convolutional neural networks
4. Attention is All you Need (Neural Information Processing Systems)
5. Long Short-Term Memory
6. Gradient-based learning applied to document recognition
7. ImageNet: A large-scale hierarchical image database
8. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
9. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
10. Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)

Their papers

• ProjE: Embedding Projection for Knowledge Graph Completion (2016) — 277 citations
• Open-World Knowledge Graph Completion (2017) — 330 citations