Peter Battaglino

Probabilistic & Bayesian Methods · 2009–2020

A researcher in the Science corpus: 2 papers; trusts 10 researchers and is trusted by 11 researchers here, as inferred from the citation graph.

Subfields

• Probabilistic & Bayesian Methods — 15 citations into it; #803 of 1,525 by trust here, #921 by citations
• Statistics and Probability — 6 citations into it
• Artificial Intelligence — 5 citations into it; #13,288 of 35,345 by trust here, #19,439 by citations

Whom Peter Battaglino trusts overall

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

1. Radford M. Neal
2. Toshiyuki TANAKA
3. Geoffrey E. Hinton
4. Aapo Hyvärinen
5. Stephen P. Boyd
6. David H. Ackley
7. David John Cameron MacKay

Who trusts Peter Battaglino overall

1. Jascha Narain Sohl-Dickstein
2. Yang Song
3. Benjamin Jackson Culpepper
4. Saeed Saremi
5. Christopher J. Hillar
6. Benigno Uria
7. Tianyu Pang
8. Tong Che

Papers from Peter Battaglino's perspective

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

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

Their papers

• Minimum Probability Flow Learning (2009) — 72 citations
• A new method for parameter estimation in probabilistic models: Minimum probability flow (2020) — 63 citations