Igor Ganichev

Artificial Intelligence · 2018–2019

A researcher in the Science corpus: 2 papers; trusts 32 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 39 citations into it
• Computer Vision and Pattern Recognition — 31 citations into it
• Model Architectures — 13 citations into it
• Natural Language Processing — 13 citations into it

Whom Igor Ganichev trusts overall

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

1. Diederik P. Kingma
2. Alex Graves
3. Yoshua Bengio
4. Geoffrey E. Hinton
5. Sepp Hochreiter
6. Sergey Ioffe
7. Jimmy Ba
8. Alex Krizhevsky
9. J. Urgen Schmidhuber
10. Ilya Sutskever

Who trusts Igor Ganichev overall

1. Aditya Mogadala

Papers from Igor Ganichev's perspective

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

1. ImageNet classification with deep convolutional neural networks
2. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
3. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. Long Short-Term Memory
5. ImageNet: A large-scale hierarchical image database
6. Gradient-based learning applied to document recognition
7. Attention is All you Need (Neural Information Processing Systems)
8. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
9. Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
10. Going deeper with convolutions

Their papers

• TensorFlow Eager: A Multi-Stage, Python-Embedded DSL for Machine Learning (2019) — 92 citations
• A dataset and architecture for visual reasoning with a working memory (2018) — 56 citations