Bettina Grün
Sociology and Political Science · 2007–2018
A researcher in the Science corpus: 11 papers; trusts 64 researchers and is trusted by 46 researchers here, as inferred from the citation graph.
Subfields
- Sociology and Political Science — 44 citations into it; #11,917 of 22,756 by trust here, #15,556 by citations
- Artificial Intelligence — 40 citations into it; #5,943 of 35,345 by trust here, #13,163 by citations
- Statistics and Probability — 31 citations into it; #2,311 of 12,932 by trust here, #4,253 by citations
- Marketing — 30 citations into it; #1,261 of 6,289 by trust here, #2,567 by citations
- Organizational Behavior and Human Resource Management — 15 citations into it; #3,158 of 8,741 by trust here, #5,674 by citations
- Probabilistic & Bayesian Methods — 12 citations into it
- Social Psychology — 11 citations into it
- Food Science — 10 citations into it; #434 of 1,700 by trust here, #1,193 by citations
Whom Bettina Grün trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Friedrich Leisch
- Arthur P. Dempster
- Chris Fraley
- David M. Blei
- Christophe Biernacki
- Sylvia Frühwirth-Schnatter
- Kurt Hornik
- Geoffrey J. McLachlan
- Nan M. Laird
- P. Deb
Who trusts Bettina Grün overall
- Isobel Claire Gormley
- Christian Kleiber
- Sylvia Frühwirth-Schnatter
- Sara Dolnicar
- Drew A. Linzer
- Bertolt Meyer
- Tatjana Miljkovic
- Margaret E. Roberts
- Jacob C. Douma
- Nicolas Städler
Papers from Bettina Grün's perspective
Ordered by how strongly the researchers Bettina Grün trusts endorse each paper. Same corpus, a different order for every researcher.
- ImageNet classification with deep convolutional neural networks
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Maximum likelihood from incomplete data via the EM - algorithm plus discussions on the paper
- Gradient-based learning applied to document recognition
- Attention is All you Need (Neural Information Processing Systems)
- Long Short-Term Memory
- Learning Multiple Layers of Features from Tiny Images
- ImageNet: A large-scale hierarchical image database
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
Their papers
- FlexMix Version 2: Finite Mixtures with Concomitant Variables and Varying and Constant Parameters (2008) — 489 citations
- Validly Measuring Destination Image in Survey Studies (2013) — 158 citations
- Can Heterogeneity Among Individuals and Contexts/ Environments Be Harvested for Improved Sustainable Management? (2009) — 224 citations
- Modeling loss data using mixtures of distributions (2016) — 107 citations
- Challenging “Factor–Cluster Segmentation” (2008) — 237 citations
- Quick, Simple and Reliable: Forced Binary Survey Questions (2011) — 129 citations
- Market Segmentation Analysis: Understanding It, Doing It, and Making It Useful (2018) — 155 citations
- Extended Beta Regression in R: Shaken, Stirred, Mixed, and Partitioned (2012) — 408 citations
- topicmodels: An R Package for Fitting Topic Models (2011) — 1,242 citations
- Finite Mixtures of Generalized Linear Regression Models (2008) — 84 citations
- Cross‐cultural differences in survey response patterns (2007) — 140 citations