Michele Minelli

Artificial Intelligence · 2018

A researcher in the Science corpus: 1 paper; trusts 4 researchers and is trusted by 2 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 23 citations into it; #30,471 of 35,345 by trust here, #22,463 by citations
• Computational Theory and Mathematics — 9 citations into it; #10,568 of 12,182 by trust here, #5,724 by citations

Whom Michele Minelli trusts overall

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

1. Yann LeCun
2. Craig Gentry
3. Vadim Lyubashevsky
4. Jaideep Vaidya
5. Chris Peikert
6. Ilaria Chillotti
7. Yoshua Bengio
8. Oded Regev
9. L. Eon Bottou

Who trusts Michele Minelli overall

1. Alon Brutzkus
2. Qinbin Li
3. Assi Barak
4. Nitin Agrawal
5. Amartya Sanyal

Papers from Michele Minelli's perspective

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

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

Their papers

• Fast Homomorphic Evaluation of Deep Discretized Neural Networks (2018) — 358 citations