J. Barnard
Nuclear and High Energy Physics · with Dawe · 2013–2016
A researcher in the Science corpus: 2 papers; trusts 17 researchers and is trusted by 4 researchers here, as inferred from the citation graph.
Subfields
- Nuclear and High Energy Physics — 50 citations into it; #4,480 of 6,161 by trust here, #4,734 by citations
- Artificial Intelligence — 11 citations into it
Whom J. Barnard trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- S. Gieseke
- Simon Plätzer
- Roberto Contino
- Jesse Thaler
- A. Larkoski
- Diederik P. Kingma
- Steffen Schumann
- Matteo Cacciari
- A. Pomarol
- K. Agashe
Who trusts J. Barnard overall
- Giacomo Cacciapaglia
- Gilles Louppe
- G. Ferretti
- Patrick T. Komiske
- Claudio Pica
- E. Metodiev
- Kyunghyun Cho
Papers from J. Barnard's perspective
Ordered by how strongly the researchers J. Barnard trusts endorse each paper. Same corpus, a different order for every researcher.
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- ImageNet classification with deep convolutional neural networks
- Gradient-based learning applied to document recognition
- Long Short-Term Memory
- The anti-$k_t$ jet clustering algorithm
- Attention is All you Need (Neural Information Processing Systems)
- Influence of cultivation temperature on the ligninolytic activity of selected fungal strains
- Learning Multiple Layers of Features from Tiny Images
- GENERATIVE ADVERSARIAL NETS
Their papers
- Parton Shower Uncertainties in Jet Substructure Analyses with Deep Neural Networks (2016) — 120 citations
- UV descriptions of composite Higgs models without elementary scalars (2013) — 219 citations