Anders Andreassen
Artificial Intelligence · 2018–2024
A researcher in the Science corpus: 7 papers; trusts 138 researchers and is trusted by 0 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 117 citations into it
- Computer Vision and Pattern Recognition — 53 citations into it
- Nuclear and High Energy Physics — 42 citations into it
- Natural Language Processing — 40 citations into it
- Large Language Models — 22 citations into it
- Model Architectures — 22 citations into it
- AI for Physical Sciences — 13 citations into it
- Optimization & Training — 11 citations into it
Whom Anders Andreassen trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Alex Krizhevsky
- Kaiming He
- Geoffrey E. Hinton
- Yoshua Bengio
- Yann LeCun
- Ilya Sutskever
- Karen Simonyan
- Christian Szegedy
- Alex Graves
- Diederik P. Kingma
Who trusts Anders Andreassen overall
- A. Larkoski
- Eric Zelikman
- Michael R Douglas
- Zhangir Azerbayev
- Xuezhi Wang
- Guohao Li
- I. Moult
- Jason Wei
- Jie Huang
- Yilun Du
Papers from Anders Andreassen's perspective
Ordered by how strongly the researchers Anders Andreassen 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)
- Long Short-Term Memory
- Attention is All you Need (Neural Information Processing Systems)
- ImageNet: A large-scale hierarchical image database
- Gradient-based learning applied to document recognition
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- ImageNet Large Scale Visual Recognition Challenge
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
Their papers
- Show Your Work: Scratchpads for Intermediate Computation with Language Models (2021) — 1,075 citations
- Solving Quantitative Reasoning Problems with Language Models (2022) — 1,845 citations
- The Evolution of Out-of-Distribution Robustness Throughout Fine-Tuning (2021) — 94 citations
- Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context (2024) — 3,818 citations
- Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language models (2022) — 2,561 citations
- Neural networks for full phase-space reweighting and parameter tuning (2019) — 111 citations
- JUNIPR: a framework for unsupervised machine learning in particle physics (2018) — 146 citations