Giacomo De Palma

Artificial Intelligence · 2018

A researcher in the Science corpus: 1 paper; trusts 13 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 42 citations into it
• Scaling & Learning Theory — 29 citations into it
• Computer Vision and Pattern Recognition — 15 citations into it
• Model Architectures — 8 citations into it
• Statistical Learning Theory — 7 citations into it

Whom Giacomo De Palma trusts overall

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

1. Jorma Rissanen
2. Temple F. Smith
3. Yann LeCun
4. J. Urgen Schmidhuber
5. Yoshua Bengio
6. Geoffrey E. Hinton
7. L. Eon Bottou
8. Amit Daniely
9. Diederik P. Kingma
10. Alex Krizhevsky

Who trusts Giacomo De Palma overall

1. Michael Hahn
2. Maximilian Pichler

Papers from Giacomo De Palma's perspective

Ordered by how strongly the researchers Giacomo De Palma 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. Long Short-Term Memory
6. Attention is All you Need (Neural Information Processing Systems)
7. ImageNet: A large-scale hierarchical image database
8. Learning Multiple Layers of Features from Tiny Images
9. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
10. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)

Their papers

• Deep neural networks are biased towards simple functions (2018) — 73 citations