Eric Laloy

Statistics and Probability · 2010–2017

A researcher in the Science corpus: 5 papers; trusts 42 researchers and is trusted by 14 researchers here, as inferred from the citation graph.

Subfields

• Statistics and Probability — 42 citations into it
• Environmental Engineering — 38 citations into it; #864 of 5,479 by trust here, #1,681 by citations
• Artificial Intelligence — 27 citations into it
• Water Science and Technology — 16 citations into it; #191 of 1,711 by trust here, #886 by citations
• Probabilistic & Bayesian Methods — 15 citations into it
• Global and Planetary Change — 13 citations into it; #1,530 of 10,225 by trust here, #6,266 by citations
• Ocean Engineering — 12 citations into it; #1,940 of 3,193 by trust here, #1,606 by citations
• Mathematical Physics — 9 citations into it

Whom Eric Laloy trusts overall

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

1. Jasper A. Vrugt
2. C. T. ter Braak
3. Gareth O. Roberts
4. Andrew Gelman
5. Heikki Haario
6. Dongbin Xiu
7. M. Tonkin
8. Youssef M. Marzouk
9. John Doherty
10. Donald B. Rubin

Who trusts Eric Laloy overall

1. Jasper A. Vrugt
2. Mojtaba Sadegh
3. Niklas Linde
4. Chaopeng Shen
5. Yinhao Zhu
6. Peigui Liu
7. Shaoxing Mo
8. Xiaoqing Shi
9. Diederik Jacques
10. Ming Ye

Papers from Eric Laloy's perspective

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

1. ImageNet classification with deep convolutional neural networks
2. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
3. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
4. Long Short-Term Memory
5. Gradient-based learning applied to document recognition
6. Attention is All you Need (Neural Information Processing Systems)
7. ImageNet: A large-scale hierarchical image database
8. Learning Multiple Layers of Features from Tiny Images
9. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
10. Inference from Iterative Simulation Using Multiple Sequences

Their papers

• Training‐Image Based Geostatistical Inversion Using a Spatial Generative Adversarial Neural Network (2017) — 345 citations
• Probabilistic inference of multi‐Gaussian fields from indirect hydrological data using circulant embedding and dimensionality reduction (2015) — 47 citations
• Efficient posterior exploration of a high‐dimensional groundwater model from two‐stage Markov chain Monte Carlo simulation and polynomial chaos expansion (2013) — 256 citations
• High‐dimensional posterior exploration of hydrologic models using multiple‐try DREAM(ZS) and high‐performance computing (2012) — 532 citations
• Parameter optimization and uncertainty analysis for plot-scale continuous modeling of runoff using a formal Bayesian approach. (2010) — 52 citations