Robert Peharz

Artificial Intelligence · 2018–2019

A researcher in the Science corpus: 2 papers; trusts 17 researchers and is trusted by 2 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 22 citations into it
• Computer Vision and Pattern Recognition — 18 citations into it
• Probabilistic & Bayesian Methods — 14 citations into it
• Representation & Self-Supervised Learning — 5 citations into it

Whom Robert Peharz trusts overall

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

1. Diederik P. Kingma
2. Geoffrey E. Hinton
3. Jorma Rissanen
4. Adnan Darwiche
5. Ruslan Salakhutdinov
6. Yann LeCun
7. Yoshua Bengio
8. Jimmy Ba
9. Alex Krizhevsky
10. John Schulman

Who trusts Robert Peharz overall

1. Hao Wang
2. Deniz Oktay

Papers from Robert Peharz's perspective

Ordered by how strongly the researchers Robert Peharz 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. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. Gradient-based learning applied to document recognition
5. Attention is All you Need (Neural Information Processing Systems)
6. Long Short-Term Memory
7. ImageNet: A large-scale hierarchical image database
8. Learning Multiple Layers of Features from Tiny Images
9. Going deeper with convolutions
10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers

• Faster Attend-Infer-Repeat with Tractable Probabilistic Models (2019) — 61 citations
• Minimal Random Code Learning: Getting Bits Back from Compressed Model Parameters (2018) — 103 citations