Andrey Malinin

Artificial Intelligence · 2017–2021

A researcher in the Science corpus: 7 papers; trusts 399 researchers and is trusted by 60 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 131 citations into it; #3,590 of 35,345 by trust here, #7,728 by citations
• Computer Vision and Pattern Recognition — 48 citations into it
• Natural Language Processing — 48 citations into it
• Safety, Robustness & Interpretability — 44 citations into it; #310 of 2,251 by trust here, #1,078 by citations
• Probabilistic & Bayesian Methods — 28 citations into it; #371 of 1,525 by trust here, #590 by citations
• Signal Processing — 21 citations into it
• Evaluation & Benchmarks — 19 citations into it
• Optimization & Training — 15 citations into it

Whom Andrey Malinin trusts overall

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

1. Alex Krizhevsky
2. Geoffrey E. Hinton
3. Diederik P. Kingma
4. Yarin Gal
5. Yann LeCun
6. Max Welling
7. Alex Graves
8. Yoshua Bengio
9. Christian Szegedy
10. Kaiming He

Who trusts Andrey Malinin overall

1. Mark John Francis Gales
2. Zhen Lin
3. Alexander Amini
4. Jeremiah Zhe Liu
5. Lorenz Kuhn
6. Yixuan Li
7. Vinod Kumar Kurmi
8. Moloud Abdar
9. Rui Huang
10. Jakob Gawlikowski

Papers from Andrey Malinin's perspective

Ordered by how strongly the researchers Andrey Malinin 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. Attention is All you Need (Neural Information Processing Systems)
5. Long Short-Term Memory
6. Gradient-based learning applied to document recognition
7. ImageNet: A large-scale hierarchical image database
8. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
9. Learning Multiple Layers of Features from Tiny Images
10. ImageNet Large Scale Visual Recognition Challenge

Their papers

• Predictive Uncertainty Estimation via Prior Networks (2018) — 1,146 citations
• Ensemble Distribution Distillation (2019) — 278 citations
• Uncertainty Estimation in Autoregressive Structured Prediction (2021) — 509 citations
• Prior Networks for Detection of Adversarial Attacks (2018) — 5 citations
• Incorporating Uncertainty into Deep Learning for Spoken Language Assessment (2017) — 47 citations
• Reverse KL-Divergence Training of Prior Networks: Improved Uncertainty and Adversarial Robustness (2019) — 227 citations
• Uncertainty Measures in Neural Belief Tracking and the Effects on Dialogue Policy Performance (2021) — 11 citations