Eric Meissner

Artificial Intelligence · 2018

A researcher in the Science corpus: 1 paper; trusts 7 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 13 citations into it
• Probabilistic & Bayesian Methods — 12 citations into it

Whom Eric Meissner trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. Michalis K. Titsias
2. Michael I. Jordan
3. S. MacEachern
4. Neil D. Lawrence
5. Andreas C. Damianou
6. Hemant Ishwaran
7. Avi Pfeffer
8. Zhenwen Dai
9. Radford M. Neal

Who trusts Eric Meissner overall

1. Bernie Wang

Papers from Eric Meissner's perspective

Ordered by how strongly the researchers Eric Meissner trusts endorse each paper. Same corpus, a different order for every researcher.

1. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
2. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
3. ImageNet classification with deep convolutional neural networks
4. Learning Multiple Layers of Features from Tiny Images
5. Gradient-based learning applied to document recognition
6. Auto-Encoding Variational Bayes (International Conference on Learning Representations)
7. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
8. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
9. Automatic differentiation in PyTorch
10. ImageNet Large Scale Visual Recognition Challenge

Their papers

• MXFusion: A Modular Deep Probabilistic Programming Library (2018) — 12 citations