Alex Tank

Artificial Intelligence · 2014–2021

A researcher in the Science corpus: 4 papers; trusts 18 researchers and is trusted by 8 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 32 citations into it; #21,605 of 35,345 by trust here, #27,551 by citations
• Economics and Econometrics — 17 citations into it
• Statistics and Probability — 17 citations into it
• Management Science and Operations Research — 11 citations into it
• Optimization & Training — 8 citations into it
• Finance — 7 citations into it
• Time-Series & Forecasting — 7 citations into it
• Control and Systems Engineering — 6 citations into it; #6,602 of 8,257 by trust here, #7,140 by citations

Whom Alex Tank trusts overall

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

1. Aapo Hyvärinen
2. Alex Graves
3. Robert Tibshirani
4. Tom Minka
5. Paul J. Werbos
6. Shohei Shimizu
7. Dahua Lin
8. Geoffrey E. Hinton
9. R. Ho
10. Helmut Ltkepohl

Who trusts Alex Tank overall

1. Ali Shojaie
2. Jason Ramapuram
3. James McInerney
4. Ghassen Jerfel
5. Maximilian Pichler
6. Mingming Gong
7. Mengdi Xu
8. Emily B. Fox
9. Rajesh Ranganath
10. Magda Gregorová

Papers from Alex Tank's perspective

Ordered by how strongly the researchers Alex Tank 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. Long Short-Term Memory
6. Attention is All you Need (Neural Information Processing Systems)
7. ImageNet: A large-scale hierarchical image database
8. Learning Multiple Layers of Features from Tiny Images
9. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
10. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)

Their papers

• Streaming Variational Inference for Bayesian Nonparametric Mixture Models (2014) — 39 citations
• A Unified Framework for Long Range and Cold Start Forecasting of Seasonal Profiles in Time Series (2017) — 6 citations
• Neural Granger Causality (2021) — 403 citations
• Identifiability and estimation of structural vector autoregressive models for subsampled and mixed-frequency time series. (2017) — 28 citations