Boris Ivanovic

Computer Vision and Pattern Recognition · 2018–2024

A researcher in the Science corpus: 3 papers; trusts 327 researchers and is trusted by 13 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 55 citations into it; #8,247 of 21,575 by trust here, #13,542 by citations
• Artificial Intelligence — 43 citations into it; #18,731 of 35,345 by trust here, #26,682 by citations
• Automotive Engineering — 38 citations into it; #437 of 3,081 by trust here, #1,602 by citations
• Model Architectures — 13 citations into it
• Generative Models — 12 citations into it
• Reinforcement Learning — 9 citations into it
• Probabilistic & Bayesian Methods — 7 citations into it
• Ocean Engineering — 6 citations into it

Whom Boris Ivanovic trusts overall

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

1. Radford M. Neal
2. Geoffrey E. Hinton
3. Yoshua Bengio
4. Sepp Hochreiter
5. Kaiming He
6. Diederik P. Kingma
7. Alex Krizhevsky
8. Dzmitry Bahdanau
9. J. Urgen Schmidhuber
10. Yann LeCun

Who trusts Boris Ivanovic overall

1. Ye Yuan
2. Tianpei Gu
3. Tim Salzmann
4. Cunjun Yu
5. Andrey Rudenko
6. Liushuai Shi
7. Xinshuo Weng
8. Karttikeya Mangalam
9. Guangyi Chen
10. Kris M. Kitani

Papers from Boris Ivanovic's perspective

Ordered by how strongly the researchers Boris Ivanovic 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. Long Short-Term Memory
5. Attention is All you Need (Neural Information Processing Systems)
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. Going deeper with convolutions
10. ImageNet Large Scale Visual Recognition Challenge

Their papers

• Trajectron++: Dynamically-Feasible Trajectory Forecasting with Heterogeneous Data (2020) — 1,349 citations
• The Trajectron: Probabilistic Multi-Agent Trajectory Modeling With Dynamic Spatiotemporal Graphs (2018) — 488 citations
• NAVSIM: Data-Driven Non-Reactive Autonomous Vehicle Simulation and Benchmarking (2024) — 348 citations