Lukasz Wesolowski
Artificial Intelligence · 2017–2021
A researcher in the Science corpus: 2 papers; trusts 42 researchers and is trusted by 1,078 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 23 citations into it; #3,621 of 35,345 by trust here, #1,452 by citations
- Computer Vision and Pattern Recognition — 21 citations into it; #1,315 of 21,575 by trust here, #1,103 by citations
- Optimization & Training — 15 citations into it; #709 of 2,601 by trust here, #149 by citations
- Computer Networks and Communications — 6 citations into it
- Hardware and Architecture — 6 citations into it
Whom Lukasz Wesolowski trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Ross B. Girshick
- Kaiming He
- Alex Krizhevsky
- Aaron M. Fewkes
- Geoffrey E. Hinton
- Shaoqing Ren
- Christian Szegedy
- Yann LeCun
- Sergey Ioffe
- Tsung-Yi Lin
Who trusts Lukasz Wesolowski overall
- Kaiming He
- Christoph Feichtenhofer
- Yang You
- Xinlei Chen
- Samuel L. Smith
- Soham De
- Jiahui Yu
- Ross B. Girshick
- Yanghao Li
- X. Wang
Papers from Lukasz Wesolowski's perspective
Ordered by how strongly the researchers Lukasz Wesolowski 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)
- ImageNet Large Scale Visual Recognition Challenge
- Going deeper with convolutions
- 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)
- Gradient-based learning applied to document recognition
- Rich Feature Hierarchies for Accurate Object Detection and Semantic Segmentation
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Attention is All you Need (Neural Information Processing Systems)
Their papers
- Accurate, Large Minibatch SGD: Training ImageNet in 1 Hour (2017) — 4,148 citations
- Datacenter-Scale Analysis and Optimization of GPU Machine Learning Workloads (2021) — 22 citations