George van den Driessche
Artificial Intelligence · 2016–2025
A researcher in the Science corpus: 10 papers; trusts 9 researchers and is trusted by 43 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 176 citations into it; #5,942 of 35,345 by trust here, #161 by citations
- Reinforcement Learning — 51 citations into it; #1,157 of 2,242 by trust here, #37 by citations
- Economics and Econometrics — 21 citations into it
- Game & Decision Theory — 14 citations into it
Whom George van den Driessche trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Richard S. Sutton
- Diederik P. Kingma
- Geoffrey E. Hinton
- Ronald J. Williams
- Rémi Coulom
- Yoshua Bengio
- Alex Krizhevsky
Who trusts George van den Driessche overall
Papers from George van den Driessche's perspective
Ordered by how strongly the researchers George van den Driessche trusts endorse each paper. Same corpus, a different order for every researcher.
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Attention is All you Need (Neural Information Processing Systems)
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- ImageNet classification with deep convolutional neural networks
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
- BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
- Going deeper with convolutions
- GENERATIVE ADVERSARIAL NETS
- Long Short-Term Memory
- Gradient-based learning applied to document recognition
Their papers
- Mastering the game of Go with deep neural networks and tree search (2016) — 19,057 citations
- Mastering the game of Go without human knowledge (2017) — 10,580 citations
- Scaling Language Models: Methods, Analysis & Insights from Training Gopher (2021) — 1,640 citations
- Training Compute-Optimal Large Language Models (2022) — 3,535 citations
- Parallel WaveNet: Fast High-Fidelity Speech Synthesis (2017) — 912 citations
- Improving language models by retrieving from trillions of tokens (2021) — 1,785 citations
- Unified Scaling Laws for Routed Language Models (2022) — 285 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
- An empirical analysis of compute-optimal large language model training (2022) — 516 citations