David M. Bortz

Artificial Intelligence · 2020

A researcher in the Science corpus: 1 paper; trusts 17 researchers and is trusted by 4 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 9 citations into it
• Statistical and Nonlinear Physics — 9 citations into it; #6,451 of 10,127 by trust here, #9,953 by citations
• Computational Mechanics — 5 citations into it; #6,734 of 10,001 by trust here, #9,862 by citations

Whom David M. Bortz trusts overall

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

1. Steven L. Brunton
2. Hayden Schaeffer
3. Kunihiko Taira
4. James P. Crutchfield
5. Aly-Khan Kassam
6. Joshua L. Proctor
7. J. Nathan Kutz
8. Maizar Raissi
9. Rebecca Killick
10. Samuel H. Rudy

Who trusts David M. Bortz overall

1. Urban Fasel

Papers from David M. Bortz's perspective

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

1. Discovering governing equations from data by sparse identification of nonlinear dynamical systems
2. Data-driven discovery of partial differential equations
3. Equations of Motion from a Data Series
4. Exact Recovery of Chaotic Systems from Highly Corrupted Data
5. The immersed boundary method: A projection approach
6. Machine learning of linear differential equations using Gaussian processes
7. Regression Shrinkage and Selection via the Lasso
8. Stop Explaining Black Box Machine Learning Models for High Stakes Decisions and Use Interpretable Models Instead
9. Predicting catastrophes in nonlinear dynamical systems by compressive sensing.
10. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)

Their papers

• WEAK SINDY FOR PARTIAL DIFFERENTIAL EQUATIONS (2020) — 297 citations