Pim de Haan
Artificial Intelligence · 2018–2019
A researcher in the Science corpus: 2 papers; trusts 59 researchers and is trusted by 0 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 43 citations into it
- Computer Vision and Pattern Recognition — 27 citations into it
- Generative Models — 22 citations into it
- Reinforcement Learning — 14 citations into it
- Probabilistic & Bayesian Methods — 8 citations into it
- Causal Inference & Discovery — 6 citations into it
- Statistics and Probability — 6 citations into it
- Management Science and Operations Research — 5 citations into it
Whom Pim de Haan trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Diederik P. Kingma
- Sergey Levine
- Geoffrey E. Hinton
- Alex Krizhevsky
- Stéphane Ross
- Yoshua Bengio
- Max Welling
- Yann LeCun
- Philipp Krahenbuhl
- Ilya Sutskever
Who trusts Pim de Haan overall
Papers from Pim de Haan's perspective
Ordered by how strongly the researchers Pim de Haan 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)
- Gradient-based learning applied to document recognition
- Long Short-Term Memory
- ImageNet: A large-scale hierarchical image database
- Learning Multiple Layers of Features from Tiny Images
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
- GENERATIVE ADVERSARIAL NETS
Their papers
- Causal Confusion in Imitation Learning (2019) — 443 citations
- Explorations in Homeomorphic Variational Auto-Encoding (2018) — 131 citations