Diego de Las Casas
Artificial Intelligence · 2018–2024
A researcher in the Science corpus: 10 papers; trusts 58 researchers and is trusted by 3 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 210 citations into it
- Computer Vision and Pattern Recognition — 121 citations into it
- Generative Models — 34 citations into it
- Optimization & Training — 28 citations into it
- Reinforcement Learning — 28 citations into it; #1,736 of 2,242 by trust here, #591 by citations
- Management Science and Operations Research — 10 citations into it
Whom Diego de Las Casas trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Diederik P. Kingma
- Geoffrey E. Hinton
- Yoshua Bengio
- Richard S. Sutton
- Ronald J. Williams
- Alex Krizhevsky
- Ilya Sutskever
- Yann LeCun
- Jimmy Ba
- Kaiming He
Who trusts Diego de Las Casas overall
Papers from Diego de Las Casas's perspective
Ordered by how strongly the researchers Diego de Las Casas trusts endorse each paper. Same corpus, a different order for every researcher.
- ImageNet classification with deep convolutional neural networks
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Attention is All you Need (Neural Information Processing Systems)
- Long Short-Term Memory
- Gradient-based learning applied to document recognition
- ImageNet: A large-scale hierarchical image database
- BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
- GENERATIVE ADVERSARIAL NETS
- Learning Multiple Layers of Features from Tiny Images
Their papers
- Scaling Language Models: Methods, Analysis & Insights from Training Gopher (2021) — 1,640 citations
- Training Compute-Optimal Large Language Models (2022) — 3,535 citations
- Improving language models by retrieving from trillions of tokens (2021) — 1,785 citations
- Transformation-based Adversarial Video Prediction on Large-Scale Data (2020) — 95 citations
- Mistral 7B (2023) — 3,685 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
- Mixtral of Experts (2024) — 2,015 citations
- An empirical analysis of compute-optimal large language model training (2022) — 516 citations
- DeepMind Control Suite (2018) — 1,440 citations