J. Garibaldi

Artificial Intelligence · 2002–2017

A researcher in the Science corpus: 3 papers; trusts 7 researchers and is trusted by 7 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 9 citations into it
• Economics and Econometrics — 7 citations into it
• Management Science and Operations Research — 7 citations into it; #9,850 of 11,946 by trust here, #9,931 by citations

Whom J. Garibaldi trusts overall

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

1. Spyros Makridakis
2. Yoshua Bengio
3. Bill Triggs

Who trusts J. Garibaldi overall

1. Heiko Hirschmüller
2. Alexei Botchkarev
3. Daniel Scharstein
4. Ruigang Yang
5. Haofei Xu

Papers from J. Garibaldi's perspective

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

1. ImageNet classification with deep convolutional neural networks
2. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
3. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
4. Gradient-based learning applied to document recognition
5. Another look at measures of forecast accuracy
6. Long Short-Term Memory
7. Attention is All you Need (Neural Information Processing Systems)
8. Practical Recommendations for Gradient-Based Training of Deep Architectures
9. Learning Multiple Layers of Features from Tiny Images
10. The M3-Competition: results, conclusions and implications

Their papers

• Real-Time Correlation-Based Stereo Vision with Reduced Border Errors (2002) — 535 citations
• A new accuracy measure based on bounded relative error for time series forecasting (2017) — 243 citations
• Can machine-learning improve cardiovascular risk prediction using routine clinical data? (2017) — 1,188 citations