Zhenwen Dai
Artificial Intelligence · 2015–2019
A researcher in the Science corpus: 5 papers; trusts 111 researchers and is trusted by 2 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 63 citations into it; #30,465 of 35,345 by trust here, #9,092 by citations
- Computer Vision and Pattern Recognition — 41 citations into it
- Probabilistic & Bayesian Methods — 38 citations into it
- Generative Models — 11 citations into it
- Optimization & Training — 11 citations into it
- Representation & Self-Supervised Learning — 10 citations into it
- Computational Theory and Mathematics — 9 citations into it
- Model Architectures — 8 citations into it
Whom Zhenwen Dai trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Michalis K. Titsias
- Neil D. Lawrence
- Diederik P. Kingma
- Geoffrey E. Hinton
- Yoshua Bengio
- Michael I. Jordan
- Alex Krizhevsky
- Yann LeCun
- Radford M. Neal
- Andreas C. Damianou
Who trusts Zhenwen Dai overall
- Hugh Salimbeni
- Bernie Wang
- Kurt Cutajar
- Marc Peter Deisenroth
- Alex Smola
- Danielle C. Maddix
- Kirthevasan Kandasamy
- Colin White
- Eric Meissner
- Liam Li
Papers from Zhenwen Dai's perspective
Ordered by how strongly the researchers Zhenwen Dai 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)
- Gradient-based learning applied to document recognition
- Long Short-Term Memory
- Attention is All you Need (Neural Information Processing Systems)
- Learning Multiple Layers of Features from Tiny Images
- ImageNet: A large-scale hierarchical image database
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- ImageNet Large Scale Visual Recognition Challenge
Their papers
- Variational Information Distillation for Knowledge Transfer (2019) — 763 citations
- Batch Bayesian Optimization via Local Penalization (2015) — 413 citations
- Variational Auto-encoded Deep Gaussian Processes (2015) — 138 citations
- MXFusion: A Modular Deep Probabilistic Programming Library (2018) — 12 citations
- Auto-Differentiating Linear Algebra (2017) — 43 citations