Krzysztof Maziarz
Artificial Intelligence · 3 papers · 2017–2019
A researcher in the Science corpus: 3 papers; trusts 151 researchers and is trusted by 8 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 81 citations into it; #16,607 of 35,345 by trust here, #2,793 by citations
- Computer Vision and Pattern Recognition — 51 citations into it; #16,442 of 21,575 by trust here, #2,148 by citations
- Model Architectures — 32 citations into it; #1,752 of 2,278 by trust here, #312 by citations
- Optimization & Training — 19 citations into it
- Neural Architecture Search & AutoML — 11 citations into it; #176 of 283 by trust here, #260 by citations
- Evaluation & Benchmarks — 8 citations into it
- Management Science and Operations Research — 7 citations into it
Whom Krzysztof Maziarz trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Quoc V. Le
- Barret Zoph
- Geoffrey E. Hinton
- Kaiming He
- Alex Krizhevsky
- Yoshua Bengio
- Ronald J. Williams
- Diederik P. Kingma
- Ilya Sutskever
- Karen Simonyan
Who trusts Krzysztof Maziarz overall
- Colin White
- Willie Neiswanger
- Yuqiao Liu
- Yash Savani
- Hongyan Tang
- Andrea Gesmundo
- Sam Nolen
- David R Ha
- Aakanksha Chowdhery
- Yanan Sun
Papers from Krzysztof Maziarz's perspective
Ordered by how strongly the researchers Krzysztof Maziarz trusts endorse each paper. Same corpus, a different order for every researcher.
- ImageNet classification with deep convolutional neural networks
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Long Short-Term Memory
- Attention is All you Need (Neural Information Processing Systems)
- ImageNet: A large-scale hierarchical image database
- Gradient-based learning applied to document recognition
- ImageNet Large Scale Visual Recognition Challenge
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
Their papers
- Outrageously Large Neural Networks: The Sparsely-Gated Mixture-of-Experts Layer (2017) — 5,113 citations
- Evolutionary-Neural Hybrid Agents for Architecture Search (2018) — 44 citations
- Gumbel-Matrix Routing for Flexible Multi-task Learning (2019) — 13 citations