Stephan Hoyer
Artificial Intelligence · 2009–2023
A researcher in the Science corpus: 12 papers; trusts 37 researchers and is trusted by 18 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 116 citations into it; #14,677 of 35,345 by trust here, #4,656 by citations
- Computer Vision and Pattern Recognition — 60 citations into it
- Atmospheric Science — 59 citations into it; #1,096 of 4,804 by trust here, #853 by citations
- Global and Planetary Change — 53 citations into it; #3,865 of 10,225 by trust here, #4,198 by citations
- Statistical and Nonlinear Physics — 37 citations into it; #5,808 of 10,127 by trust here, #2,437 by citations
- Optimization & Training — 26 citations into it
- Molecular Biology — 21 citations into it; #12,443 of 17,773 by trust here, #15,850 by citations
- Atomic and Molecular Physics, and Optics — 20 citations into it; #5,094 of 7,135 by trust here, #6,080 by citations
Whom Stephan Hoyer trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Andris Ambainis
- Akihito Ishizaki
- Martin Bodo Plenio
- Graham R. Fleming
- Julian Adolphs
- Filippo Caruso
- Patrick Rebentrost
- Diederik P. Kingma
- Alex Krizhevsky
- Mohan Sarovar
Who trusts Stephan Hoyer overall
- I. Pisso
- Seogjoo J. Jang
- L. Gregor
- Tung Nguyen
- Johannes Brandstetter
- Benedetta Mennucci
- Schalk Kok
- Maialen Iturbide
- Ricardo Vinuesa
- Philipp Holl
Papers from Stephan Hoyer's perspective
Ordered by how strongly the researchers Stephan Hoyer trusts endorse each paper. Same corpus, a different order for every researcher.
- ImageNet classification with deep convolutional neural networks
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Attention is All you Need (Neural Information Processing Systems)
- ImageNet: A large-scale hierarchical image database
- Gradient-based learning applied to document recognition
- Long Short-Term Memory
- GENERATIVE ADVERSARIAL NETS
- Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
- ImageNet Large Scale Visual Recognition Challenge
Their papers
- Array programming with NumPy (2020) — 21,287 citations
- Efficient and Modular Implicit Differentiation (2021) — 360 citations
- Limits of quantum speedup in photosynthetic light harvesting (2009) — 155 citations
- Learning skillful medium-range global weather forecasting (2023) — 1,707 citations
- Neural general circulation models for weather and climate (2023) — 507 citations
- WeatherBench 2: A Benchmark for the Next Generation of Data‐Driven Global Weather Models (2023) — 360 citations
- GraphCast: Learning skillful medium-range global weather forecasting (2022) — 419 citations
- Machine learning–accelerated computational fluid dynamics (2021) — 1,218 citations
- Lagrangian Neural Networks (2020) — 615 citations
- Learning data-driven discretizations for partial differential equations (2018) — 609 citations
- xarray: N-D labeled arrays and datasets in Python (2017) — 1,262 citations
- The Cramer Distance as a Solution to Biased Wasserstein Gradients (2017) — 397 citations