Alexander Amini

Computer Vision and Pattern Recognition · 2018–2022

A researcher in the Science corpus: 6 papers; trusts 266 researchers and is trusted by 3 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 93 citations into it
• Artificial Intelligence — 77 citations into it
• Aerospace Engineering — 42 citations into it
• Model Architectures — 23 citations into it
• Automotive Engineering — 18 citations into it; #1,932 of 3,081 by trust here, #2,332 by citations
• Probabilistic & Bayesian Methods — 18 citations into it
• Reinforcement Learning — 14 citations into it
• Safety, Robustness & Interpretability — 12 citations into it

Whom Alexander Amini trusts overall

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

1. Diederik P. Kingma
2. Geoffrey E. Hinton
3. Alex Krizhevsky
4. Alex Graves
5. Yoshua Bengio
6. Kaiming He
7. Yann LeCun
8. Ilya Sutskever
9. Dean A. Pomerleau
10. Yarin Gal

Who trusts Alexander Amini overall

1. Wilko Schwarting
2. Ava P. Soleimany
3. Di Feng
4. David Gray Widder
5. Ninareh Mehrabi
6. Daniela Rus
7. Ali Harakeh
8. Dawn Nafus

Papers from Alexander Amini's perspective

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

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

Their papers

• BEVFusion: Multi-Task Multi-Sensor Fusion with Unified Bird's-Eye View Representation (2022) — 1,613 citations
• Variational End-to-End Navigation and Localization (2018) — 124 citations
• Liquid Time-constant Networks (2020) — 462 citations
• Deep Evidential Regression (2019) — 700 citations
• Uncovering and Mitigating Algorithmic Bias through Learned Latent Structure (2019) — 216 citations
• Variational Autoencoder for End-to-End Control of Autonomous Driving with Novelty Detection and Training De-biasing (2018) — 83 citations