M. P. Stumpf
Molecular Biology · 2000–2016
A researcher in the Science corpus: 10 papers; trusts 30 researchers and is trusted by 38 researchers here, as inferred from the citation graph.
Subfields
- Molecular Biology — 78 citations into it; #3,639 of 17,773 by trust here, #5,968 by citations
- Artificial Intelligence — 31 citations into it; #11,689 of 35,345 by trust here, #10,430 by citations
- Statistics and Probability — 18 citations into it; #3,561 of 12,932 by trust here, #1,860 by citations
- Probabilistic & Bayesian Methods — 14 citations into it
- Computational Theory and Mathematics — 12 citations into it; #6,771 of 12,182 by trust here, #3,218 by citations
- Statistical and Nonlinear Physics — 11 citations into it; #3,182 of 10,127 by trust here, #1,990 by citations
- Epidemiology — 5 citations into it
Whom M. P. Stumpf trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- John K. Kruschke
- Kevin P. Murphy
- Liam Paninski
- Darren J. Wilkinson
- K. Burnham
- Vladislav Vyshemirsky
- Adam A. Margolin
- Daniel Marbach
- Chris J. Oates
- Patrick E. Meyer
Who trusts M. P. Stumpf overall
- Oliver Mason
- Mark S. Handcock
- Jure Leskovec
- M. Gould
- Peter Csermely
- Miguel Angel Muñoz
- Colin S. Gillespie
- G. Pyke
- S. Piantadosi
- MARK A. Beaumont
Papers from M. P. Stumpf's perspective
Ordered by how strongly the researchers M. P. Stumpf trusts endorse each paper. Same corpus, a different order for every researcher.
- Information Theory: 1948-1998 - Guest Editorial
- Discovering functional relationships between RNA expression and chemotherapeutic susceptibility using relevance networks. (Proceedings of the National Academy of Sciences of the United States of America)
- Monte Carlo Sampling Methods Using Markov Chains and Their Applications
- 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
- Reversible jump Markov chain Monte Carlo computation and Bayesian model determination
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Estimation of Entropy and Mutual Information
- ARACNE: An Algorithm for the Reconstruction of Gene Regulatory Networks in a Mammalian Cellular Context (BMC Bioinformatics)
Their papers
- Approximate Bayesian computation scheme for parameter inference and model selection in dynamical systems (2009) — 1,655 citations
- Estimating the size of the human interactome (2008) — 789 citations
- Subnets of scale-free networks are not scale-free: sampling properties of networks. (2005) — 578 citations
- Simulation-based model selection for dynamical systems in systems and population biology (2009) — 306 citations
- Critical Truths About Power Laws (2012) — 618 citations
- Gene Regulatory Network Inference from Single-Cell Data Using Multivariate Information Measures (2016) — 541 citations
- Topological sensitivity analysis for systems biology (2014) — 100 citations
- Statistical inference of the time-varying structure of gene-regulation networks (2010) — 948 citations
- Evolution of pathogenicity and sexual reproduction in eight Candida genomes (2009) — 1,036 citations
- Species-Area Relations in Tropical Forests (2000) — 98 citations