Esmeralda S. Whitammer
Computer Vision and Pattern Recognition · 2022–2023
A researcher in the Science corpus: 2 papers; trusts 55 researchers and is trusted by 0 researchers here, as inferred from the citation graph.
Subfields
- Computer Vision and Pattern Recognition — 44 citations into it
- Artificial Intelligence — 35 citations into it
- Generative Models — 34 citations into it
- Statistical and Nonlinear Physics — 20 citations into it
- Signal Processing — 14 citations into it
- Probabilistic & Bayesian Methods — 11 citations into it
- Biophysics — 9 citations into it
- Molecular Biology — 9 citations into it
Whom Esmeralda S. Whitammer trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Diederik P. Kingma
- Geoffrey E. Hinton
- Jonathan Ho
- Max Welling
- Alex Krizhevsky
- Yoshua Bengio
- Prafulla Dhariwal
- Kaiming He
- Yang Song
- Alex Nichol
Who trusts Esmeralda S. Whitammer overall
Papers from Esmeralda S. Whitammer's perspective
Ordered by how strongly the researchers Esmeralda S. Whitammer 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)
- Gradient-based learning applied to document recognition
- ImageNet: A large-scale hierarchical image database
- Long Short-Term Memory
- GENERATIVE ADVERSARIAL NETS
- Learning Multiple Layers of Features from Tiny Images
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
Their papers
- Improving and generalizing flow-based generative models with minibatch optimal transport (2023) — 889 citations
- Diffusion models as plug-and-play priors (2022) — 309 citations