Edward Moroshko

Artificial Intelligence · 2019–2023

A researcher in the Science corpus: 3 papers; trusts 6 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 73 citations into it
• Optimization & Training — 35 citations into it
• Computational Mechanics — 22 citations into it
• Meta & Continual Learning — 19 citations into it
• Statistics and Probability — 8 citations into it

Whom Edward Moroshko trusts overall

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

1. Geoffrey E. Hinton
2. Yoshua Bengio
3. Alex Krizhevsky
4. Anthony V. Robins
5. Ian J. Goodfellow
6. Yann LeCun
7. Kaiming He
8. Shai Shalev-Shwartz
9. Diederik P. Kingma
10. Rahaf Aljundi

Who trusts Edward Moroshko overall

1. Liangzu Peng

Papers from Edward Moroshko's perspective

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

1. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
2. ImageNet classification with deep convolutional neural networks
3. Gradient-based learning applied to document recognition
4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
5. Attention is All you Need (Neural Information Processing Systems)
6. ImageNet: A large-scale hierarchical image database
7. Long Short-Term Memory
8. Learning Multiple Layers of Features from Tiny Images
9. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
10. ImageNet Large Scale Visual Recognition Challenge

Their papers

• Kernel and Rich Regimes in Overparametrized Models (2019) — 437 citations
• Continual Learning in Linear Classification on Separable Data (2023) — 33 citations
• How catastrophic can catastrophic forgetting be in linear regression? (2022) — 90 citations