Preetam Nandy

Statistics and Probability · 2014–2016

A researcher in the Science corpus: 3 papers; trusts 39 researchers and is trusted by 17 researchers here, as inferred from the citation graph.

Subfields

• Statistics and Probability — 36 citations into it; #3,247 of 12,932 by trust here, #4,253 by citations
• Artificial Intelligence — 33 citations into it; #10,522 of 35,345 by trust here, #20,377 by citations
• Causal Inference & Discovery — 14 citations into it
• Probabilistic & Bayesian Methods — 11 citations into it
• Molecular Biology — 8 citations into it
• Information Systems — 6 citations into it
• Statistical Learning Theory — 5 citations into it

Whom Preetam Nandy trusts overall

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

1. Marloes H. Maathuis
2. David Maxwell Chickering
3. Markus Kalisch
4. Christopher Meek
5. Diego Colombo
6. Peter Buhlmann
7. Nicolai Meinshausen
8. Judea Pearl
9. Tom L. Burr
10. Han Liu

Who trusts Preetam Nandy overall

1. Mathias Drton
2. Marloes H. Maathuis
3. Christina Heinze-Deml
4. Diviyan Kalainathan
5. Olivier Goudet
6. Jack Kuipers
7. Leonard Henckel
8. Niklas Pfister
9. Neville Kenneth Kitson
10. Nicolai Meinshausen

Papers from Preetam Nandy's perspective

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

1. Regression Shrinkage and Selection via the Lasso
2. High-dimensional graphs and variable selection with the Lasso
3. Equivalence and Synthesis of Causal Models
4. Causality : Models , Reasoning , and Inference
5. Learning Equivalence Classes of Bayesian Network Structures
6. Optimal Structure Identification With Greedy Search
7. Maximum likelihood from incomplete data via the EM - algorithm plus discussions on the paper
8. Estimating the Dimension of a Model
9. ImageNet classification with deep convolutional neural networks
10. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)

Their papers

• Large-Sample Theory for the Bergsma-Dassios Sign Covariance (2016) — 35 citations
• Estimating the effect of joint interventions from observational data in sparse high-dimensional settings (2014) — 89 citations
• High-dimensional consistency in score-based and hybrid structure learning (2015) — 151 citations