Matthew D. Parno

Artificial Intelligence · 2016

A researcher in the Science corpus: 1 paper; trusts 16 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 21 citations into it
• Statistics and Probability — 20 citations into it
• Probabilistic & Bayesian Methods — 10 citations into it
• Applied Mathematics — 8 citations into it
• Geometry and Topology — 6 citations into it
• Optimization & Training — 6 citations into it

Whom Matthew D. Parno trusts overall

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

1. Cédric Villani
2. Jun S. Liu
3. Andrew Gelman
4. Pierre Del Moral
5. Mark A. Girolami
6. Jorge Nocedal
7. Esteban G. Tabak
8. Wolfgang Bangerth
9. Tarek A. El-Moselhy

Papers from Matthew D. Parno's perspective

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

1. Sequential Monte Carlo samplers
2. Sequential Monte Carlo Methods in Practice
3. Riemann manifold Langevin and Hamiltonian Monte Carlo methods
4. Monte Carlo strategies in scientific computing
5. Topics in Optimal Transportation
6. Optimal Transport: Old and New
7. Simulating Normalizing Constants: From Importance Sampling to Bridge Sampling to Path Sampling
8. Existence and uniqueness of monotone measure-preserving maps
9. Graphical Models, Exponential Families, and Variational Inference
10. Inverse problems: A Bayesian perspective (Acta Numerica)

Their papers

• An introduction to sampling via measure transport (2016) — 97 citations