Sandra Jeanne Vollmer
Artificial Intelligence · 2008–2018
A researcher in the Science corpus: 8 papers; trusts 80 researchers and is trusted by 18 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 56 citations into it; #13,130 of 35,345 by trust here, #17,776 by citations
- Statistics and Probability — 52 citations into it; #3,741 of 12,932 by trust here, #4,650 by citations
- Probabilistic & Bayesian Methods — 38 citations into it
- Economics and Econometrics — 26 citations into it; #16,222 of 23,481 by trust here, #20,008 by citations
- Optimization & Training — 23 citations into it
- Computer Vision and Pattern Recognition — 15 citations into it
- Sociology and Political Science — 13 citations into it
- Statistical and Nonlinear Physics — 11 citations into it
Whom Sandra Jeanne Vollmer trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Gareth O. Roberts
- Martin Hairer
- P. Pedroni
- Radford M. Neal
- Geoffrey E. Hinton
- Max Welling
- J. Breitung
- Alex Krizhevsky
- Diederik P. Kingma
- Michael I. Jordan
Who trusts Sandra Jeanne Vollmer overall
- Surajit Ray
- Matthias Sachs
- Deborshee Sen
- Alain Oliviero Durmus
- Jackson Gorham
- Rémi Bardenet
- George Deligiannidis
- Christopher Nemeth
- Arnaud Doucet
- Arnaud Guillin
Papers from Sandra Jeanne Vollmer's perspective
Ordered by how strongly the researchers Sandra Jeanne Vollmer 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
- Learning Multiple Layers of Features from Tiny Images
- Long Short-Term Memory
- Attention is All you Need (Neural Information Processing Systems)
- ImageNet: A large-scale hierarchical image database
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
Their papers
- Distributed Bayesian Learning with Stochastic Natural Gradient Expectation Propagation and the Posterior Server (2015) — 73 citations
- Measuring Sample Quality with Diffusions (2016) — 123 citations
- The Bouncy Particle Sampler: A Nonreversible Rejection-Free Markov Chain Monte Carlo Method (2015) — 258 citations
- Spectral gaps for a Metropolis–Hastings algorithm in infinite dimensions (2011) — 206 citations
- Inequality and growth: evidence from panel cointegration (2011) — 229 citations
- A likelihood ratio test for bimodality in two-component mixtures with application to regional income distribution in the EU (2008) — 51 citations
- Global Economic Burden of Diabetes in Adults: Projections From 2015 to 2030 (2018) — 972 citations
- The global economic burden of diabetes in adults aged 20-79 years: a cost-of-illness study. (2017) — 680 citations