Lior Hirschfeld

Artificial Intelligence · 2020

A researcher in the Science corpus: 1 paper; trusts 3 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 5 citations into it

Whom Lior Hirschfeld trusts overall

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

1. Leo Breiman
2. Thomas G. Dietterich
3. Yarin Gal
4. Wen-bing Huang
5. Zoubin Ghahramani
6. Andreas S. Weigend
7. Kevin Yang
8. Geoffrey E. Hinton

Papers from Lior Hirschfeld's perspective

Ordered by how strongly the researchers Lior Hirschfeld 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. Gradient-based learning applied to document recognition
5. ImageNet: A large-scale hierarchical image database
6. Long Short-Term Memory
7. ImageNet Large Scale Visual Recognition Challenge
8. Attention is All you Need (Neural Information Processing Systems)
9. Learning Multiple Layers of Features from Tiny Images
10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers

• Uncertainty Quantification Using Neural Networks for Molecular Property Prediction (2020) — 259 citations