Miles Lubin
Numerical Analysis · 2013–2022
A researcher in the Science corpus: 7 papers; trusts 30 researchers and is trusted by 16 researchers here, as inferred from the citation graph.
Subfields
- Numerical Analysis — 24 citations into it; #765 of 3,586 by trust here, #800 by citations
- Computational Theory and Mathematics — 21 citations into it
- Artificial Intelligence — 15 citations into it
- Electrical and Electronic Engineering — 12 citations into it
- Computer Networks and Communications — 9 citations into it; #2,121 of 9,886 by trust here, #3,228 by citations
- Hardware and Architecture — 9 citations into it; #228 of 1,551 by trust here, #471 by citations
- Computational Mechanics — 6 citations into it
- Management Science and Operations Research — 5 citations into it
Whom Miles Lubin trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Michael Grant
- Johan Efberg
- Iain Dunning
- Stephen P. Boyd
- Tobias Achterberg
- William E. Hart
- Jeff Bezanson
- Steven Diamond
- Andreas Wächter
- Richard H. Byrd
Who trusts Miles Lubin overall
- Velibor V. Misic
- Dimitris J. Bertsimas
- Jackson Gorham
- Dragos Florin Ciocan
- Jack Dunn
- Ryan Giordano
- Shuvomoy Das Gupta
- Jeff Bezanson
- Lester W. Mackey
- Tamara Broderick
Papers from Miles Lubin's perspective
Ordered by how strongly the researchers Miles Lubin trusts endorse each paper. Same corpus, a different order for every researcher.
- GAMS -- A User's Guide
- Evaluating derivatives - principles and techniques of algorithmic differentiation, Second Edition
- Disciplined Convex Programming
- LLVM: a compilation framework for lifelong program analysis & transformation
- YALMIP : a toolbox for modeling and optimization in MATLAB
- Introduction to Stochastic Programming
- Introduction to linear optimization
- Pyomo: modeling and solving mathematical programs in Python (Mathematical Programming Computation)
- Benchmarking optimization software with performance profiles
- The NumPy Array: A Structure for Efficient Numerical Computation
Their papers
- PowerModels.J1: An Open-Source Framework for Exploring Power Flow Formulations (2017) — 303 citations
- JuMP 1.0: recent improvements to a modeling language for mathematical optimization (2022) — 450 citations
- Forward-Mode Automatic Differentiation in Julia (2016) — 445 citations
- Polyhedral approximation in mixed-integer convex optimization (2016) — 64 citations
- JuMP: A Modeling Language for Mathematical Optimization (2015) — 1,563 citations
- Uncertainty Sets for Wind Power Generation (2015) — 94 citations
- Computing in Operations Research Using Julia (2013) — 361 citations