Peter Broecker

Atomic and Molecular Physics, and Optics · 2016

A researcher in the Science corpus: 1 paper; trusts 3 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Atomic and Molecular Physics, and Optics — 8 citations into it

Whom Peter Broecker trusts overall

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

1. Alex Krizhevsky
2. Giuseppe Carleo
3. Matthias Troyer
4. Lei Wang
5. L. Balents
6. Martín Abadi

Papers from Peter Broecker's perspective

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

1. Learning Multiple Layers of Features from Tiny Images
2. ImageNet classification with deep convolutional neural networks
3. Long Short-Term Memory
4. Gradient-based learning applied to document recognition
5. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
6. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
7. TensorFlow: Large-Scale Machine Learning on Heterogeneous Distributed Systems
8. ImageNet: A large-scale hierarchical image database
9. This PDF file includes: Materials and Methods
10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers

• Machine learning quantum phases of matter beyond the fermion sign problem (2016) — 310 citations