Tim Pearce
Artificial Intelligence · 2018–2023
A researcher in the Science corpus: 2 papers; trusts 9 researchers and is trusted by 2 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 31 citations into it; #30,923 of 35,345 by trust here, #31,361 by citations
- Computer Vision and Pattern Recognition — 18 citations into it
- Generative Models — 8 citations into it
- Probabilistic & Bayesian Methods — 8 citations into it
- Statistical and Nonlinear Physics — 5 citations into it; #8,708 of 10,127 by trust here, #8,564 by citations
Whom Tim Pearce trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Jonathan Ho
- Geoffrey E. Hinton
- Diederik P. Kingma
- Abbas Khosravi
- Alex Graves
- Yoshua Bengio
- Alex Krizhevsky
- Prafulla Dhariwal
- J. Urgen Schmidhuber
- Yann LeCun
Who trusts Tim Pearce overall
Papers from Tim Pearce's perspective
Ordered by how strongly the researchers Tim Pearce trusts endorse each paper. Same corpus, a different order for every researcher.
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- ImageNet classification with deep convolutional neural networks
- Attention is All you Need (Neural Information Processing Systems)
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Long Short-Term Memory
- ImageNet: A large-scale hierarchical image database
- Gradient-based learning applied to document recognition
- GENERATIVE ADVERSARIAL NETS
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
- Learning Multiple Layers of Features from Tiny Images
Their papers
- Imitating Human Behaviour with Diffusion Models (2023) — 323 citations
- High-Quality Prediction Intervals for Deep Learning: A Distribution-Free, Ensembled Approach (2018) — 334 citations