Seb Noury
Artificial Intelligence · 2017–2025
A researcher in the Science corpus: 8 papers; trusts 13 researchers and is trusted by 27 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 110 citations into it; #7,751 of 35,345 by trust here, #1,544 by citations
- Reinforcement Learning — 66 citations into it
- Computer Vision and Pattern Recognition — 56 citations into it
Whom Seb Noury trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
Who trusts Seb Noury overall
- Ye Jia
- Yu Zhang
- Heiga Zen
- Ron J. Weiss
- Takuma Okamoto
- Wei Ping
- Kainan Peng
- Xu Tan
- Zhen Zeng
- Jean-Marc Valin
Papers from Seb Noury's perspective
Ordered by how strongly the researchers Seb Noury trusts endorse each paper. Same corpus, a different order for every researcher.
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Long Short-Term Memory
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Attention is All you Need (Neural Information Processing Systems)
- ImageNet classification with deep convolutional neural networks
- Going deeper with convolutions
- GENERATIVE ADVERSARIAL NETS
- Distilling the Knowledge in a Neural Network (arXiv.org)
- Gradient-based learning applied to document recognition
- Layer Normalization
Their papers
- Parallel WaveNet: Fast High-Fidelity Speech Synthesis (2017) — 912 citations
- Efficient Neural Audio Synthesis (2018) — 936 citations
- V-MPO: On-Policy Maximum a Posteriori Policy Optimization for Discrete and Continuous Control (2019) — 141 citations
- Stabilizing Transformers for Reinforcement Learning (2019) — 486 citations
- Using Unity to Help Solve Intelligence (2020) — 23 citations
- Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context (2024) — 3,818 citations
- Gemini 2.5: Pushing the Frontier with Advanced Reasoning, Multimodality, Long Context, and Next Generation Agentic Capabilities (2025) — 3,609 citations
- Magnetic control of tokamak plasmas through deep reinforcement learning (2022) — 923 citations