Matthias Broecheler

Artificial Intelligence · 2015

A researcher in the Science corpus: 2 papers; trusts 31 researchers and is trusted by 4 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 38 citations into it; #22,710 of 35,345 by trust here, #17,412 by citations
• Probabilistic & Bayesian Methods — 26 citations into it
• Optimization & Training — 13 citations into it
• Computational Theory and Mathematics — 9 citations into it
• Computer Vision and Pattern Recognition — 8 citations into it
• Computer Networks and Communications — 7 citations into it
• Information Systems — 7 citations into it
• Management Science and Operations Research — 7 citations into it

Whom Matthias Broecheler trusts overall

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

1. Michael Collins
2. Martin J. Wainwright
3. Alexander Schrijver
4. Pedro M. Domingos
5. Solomon Eyal Shimony
6. Ruslan Salakhutdinov
7. Thorsten Joachims
8. Julian Besag
9. Geoffrey E. Hinton
10. Matthew Richardson

Who trusts Matthias Broecheler overall

1. Ivan Donadello
2. Sarasi Lalithsena
3. Leon Weber
4. Somak Aditya
5. Kosetsu Tsukuda
6. Theodoros Rekatsinas
7. A.S. d'Avila Garcez
8. Luciano Serafini
9. Zhiting Hu
10. Giuseppe Marra

Papers from Matthias Broecheler's perspective

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

1. ImageNet classification with deep convolutional neural networks
2. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
3. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. Gradient-based learning applied to document recognition
5. Long Short-Term Memory
6. Attention is All you Need (Neural Information Processing Systems)
7. ImageNet: A large-scale hierarchical image database
8. Learning Multiple Layers of Features from Tiny Images
9. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
10. Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)

Their papers

• Hinge-Loss Markov Random Fields and Probabilistic Soft Logic (2015) — 423 citations
• Hinge-Loss Markov Random Fields and Probabilistic Soft Logic (2015)