Bodhisattva Sen
Statistics and Probability · 2007–2020
A researcher in the Science corpus: 14 papers; trusts 115 researchers and is trusted by 39 researchers here, as inferred from the citation graph.
Subfields
- Statistics and Probability — 185 citations into it; #1,259 of 12,932 by trust here, #1,781 by citations
- Artificial Intelligence — 65 citations into it; #17,815 of 35,345 by trust here, #22,463 by citations
- Statistical Learning Theory — 34 citations into it
- Applied Mathematics — 32 citations into it; #5,349 of 7,620 by trust here, #7,035 by citations
- Finance — 20 citations into it
- Computational Mechanics — 13 citations into it; #1,452 of 10,001 by trust here, #2,942 by citations
- Management Science and Operations Research — 13 citations into it
- Astronomy and Astrophysics — 12 citations into it; #8,233 of 10,964 by trust here, #7,638 by citations
Whom Bodhisattva Sen trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Arthur Gretton
- G'abor J. Sz'ekely
- Moulinath Banerjee
- Maria L. Rizzo
- Michael R. Kosorok
- Bradley Efron
- Sara A. van de Geer
- Jerome H. Friedman
- Kenji Fukumizu
- Cun-Hui Zhang
Who trusts Bodhisattva Sen overall
- Adityanand Guntuboyina
- Pierre C. Bellec
- Hongjian Shi
- Promit Ghosal
- Yining Chen
- Lauren Hannah
- Cécile Durot
- Richard J. Samworth
- Nabarun Deb
- Mathias Drton
Papers from Bodhisattva Sen's perspective
Ordered by how strongly the researchers Bodhisattva Sen trusts endorse each paper. Same corpus, a different order for every researcher.
- ImageNet classification with deep convolutional neural networks
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Regression Shrinkage and Selection via the Lasso
- Learning Multiple Layers of Features from Tiny Images
- Gradient-based learning applied to document recognition
- Long Short-Term Memory
- Attention is All you Need (Neural Information Processing Systems)
- GENERATIVE ADVERSARIAL NETS
- ImageNet: A large-scale hierarchical image database
Their papers
- On Testing Independence and Goodness-of-fit in Linear Models (2013) — 55 citations
- Nonparametric Least Squares Estimation of a Multivariate Convex Regression Function (2010) — 175 citations
- Global risk bounds and adaptation in univariate convex regression (2013) — 87 citations
- Multivariate Rank-Based Distribution-Free Nonparametric Testing Using Measure Transportation (2019) — 175 citations
- On risk bounds in isotonic and other shape restricted regression problems (2013) — 143 citations
- On matrix estimation under monotonicity constraints (2015) — 62 citations
- Measuring Association on Topological Spaces Using Kernels and Geometric Graphs (2020) — 69 citations
- Inconsistency of bootstrap: The Grenander estimator (2010) — 116 citations
- Covering Numbers for Convex Functions (2012) — 76 citations
- Nonparametric Shape-Restricted Regression (2017) — 79 citations
- Multivariate ranks and quantiles using optimal transport: Consistency, rates and nonparametric testing (2019) — 79 citations
- Divide and conquer in nonstandard problems and the super-efficiency phenomenon (2016) — 68 citations
- Estimation of a two‐component mixture model with applications to multiple testing (2012) — 61 citations
- Velocity Dispersion Profiles of Seven Dwarf Spheroidal Galaxies (2007) — 268 citations