Adam Leach
Computer Vision and Pattern Recognition · 2021–2022
A researcher in the Science corpus: 2 papers; trusts 498 researchers and is trusted by 0 researchers here, as inferred from the citation graph.
Subfields
- Computer Vision and Pattern Recognition — 171 citations into it
- Generative Models — 160 citations into it
- Artificial Intelligence — 137 citations into it
- Probabilistic & Bayesian Methods — 56 citations into it
- Statistical and Nonlinear Physics — 48 citations into it
- Signal Processing — 29 citations into it
- Model Architectures — 25 citations into it
- Biophysics — 14 citations into it
Whom Adam Leach trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Diederik P. Kingma
- Geoffrey E. Hinton
- Yoshua Bengio
- Alex Krizhevsky
- Kaiming He
- Yann LeCun
- Ilya Sutskever
- Max Welling
- Radford M. Neal
- Alex Graves
Who trusts Adam Leach overall
Papers from Adam Leach's perspective
Ordered by how strongly the researchers Adam Leach 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
- 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
- Learning Multiple Layers of Features from Tiny Images
- GENERATIVE ADVERSARIAL NETS
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)