Adam Scherlis
Artificial Intelligence · with Bauman · 2018–2022
A researcher in the Science corpus: 2 papers; trusts 17 researchers and is trusted by 3 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 53 citations into it; #17,187 of 35,345 by trust here, #21,878 by citations
- Computer Vision and Pattern Recognition — 19 citations into it; #10,882 of 21,575 by trust here, #18,782 by citations
- Scaling & Learning Theory — 7 citations into it
- Optimization & Training — 6 citations into it; #1,521 of 2,601 by trust here, #2,313 by citations
Whom Adam Scherlis trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Alex Krizhevsky
- Kaiming He
- Xavier Glorot
- Yoshua Bengio
- Geoffrey E. Hinton
- Yann LeCun
- Ian J. Goodfellow
- X. Zhang
- Diederik P. Kingma
- Chunyuan Li
Who trusts Adam Scherlis overall
Papers from Adam Scherlis's perspective
Ordered by how strongly the researchers Adam Scherlis 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)
- Learning Multiple Layers of Features from Tiny Images
- Gradient-based learning applied to document recognition
- Attention is All you Need (Neural Information Processing Systems)
- Long Short-Term Memory
- ImageNet: A large-scale hierarchical image database
- ImageNet Large Scale Visual Recognition Challenge
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
Their papers
- The Goldilocks zone: Towards better understanding of neural network loss landscapes (2018) — 60 citations
- Adversarial Training for High-Stakes Reliability (2022) — 79 citations