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Scientific computing is increasingly incorporating the advancements in machine learning and the ability to work with large amounts of data. At the same time, machine learning models are becoming increasingly sophisticated and exhibit many…

Programming Languages · Computer Science 2019-07-19 Mike Innes , Alan Edelman , Keno Fischer , Chris Rackauckas , Elliot Saba , Viral B Shah , Will Tebbutt

Probabilistic Programming Languages (PPLs) are a powerful tool in machine learning, allowing highly expressive generative models to be expressed succinctly. They couple complex inference algorithms, implemented by the language, with an…

Programming Languages · Computer Science 2020-10-19 Alexander Collins , Vinod Grover

This year marks the consolidation of Julia (https://julialang.org/), a programming language designed for scientific computing, as the first stable version (1.0) has been released, in August 2018. Among its main features, expressiveness and…

Instrumentation and Methods for Astrophysics · Physics 2018-12-05 Maurizio Tomasi , Mosè Giordano

Program synthesis -- the automatic generation of code given a specification -- is one of the most fundamental tasks in artificial intelligence (AI) and the dream of many programmers. Numerous synthesizers have been developed for program…

Bridging cultures that have often been distant, Julia combines expertise from the diverse fields of computer science and computational science to create a new approach to numerical computing. Julia is designed to be easy and fast. Julia…

Mathematical Software · Computer Science 2015-07-21 Jeff Bezanson , Alan Edelman , Stefan Karpinski , Viral B. Shah

Julia is a mature general-purpose programming language, with a large ecosystem of libraries and more than 12000 third-party packages, which specifically targets scientific computing. As a language, Julia is as dynamic, interactive, and…

JuMP is an open-source modeling language that allows users to express a wide range of optimization problems (linear, mixed-integer, quadratic, conic-quadratic, semidefinite, and nonlinear) in a high-level, algebraic syntax. JuMP takes…

Optimization and Control · Mathematics 2017-05-08 Iain Dunning , Joey Huchette , Miles Lubin

Accurate and efficient methods to simulate nonadiabatic and quantum nuclear effects in high-dimensional and dissipative systems are crucial for the prediction of chemical dynamics in condensed phase. To facilitate effective development,…

Progressive Hedging is a popular decomposition algorithm for solving multi-stage stochastic optimization problems. A computational bottleneck of this algorithm is that all scenario subproblems have to be solved at each iteration. In this…

Distributed, Parallel, and Cluster Computing · Computer Science 2020-09-28 Gilles Bareilles , Yassine Laguel , Dmitry Grishchenko , Franck Iutzeler , Jérôme Malick

The Julia programming language continues to gain popularity both for its potential for programmer productivity and for its impressive performance on scientific code. It thus holds potential for large-scale HPC, but we have not yet seen this…

Distributed, Parallel, and Cluster Computing · Computer Science 2021-09-30 Amal Rizvi , Kyle C. Hale

Since time immemorial an old adage has always seemed to ring true: you cannot use a high-level productive programming language like Python or R for real-time control and embedded-systems programming, you must rewrite your program in C. We…

Systems and Control · Electrical Eng. & Systems 2025-02-10 Fredrik Bagge Carlson , Cody Tapscott , Gabriel Baraldi , Chris Rackauckas

We propose a computational framework to quantify (measure) and to optimize the reliability of complex systems. The approach uses a graph representation of the system that is subject to random failures of its components (nodes and edges).…

Optimization and Control · Mathematics 2021-06-25 Joshua L. Pulsipher , Victor M. Zavala

To model combinatorial decision problems involving uncertainty and probability, we introduce stochastic constraint programming. Stochastic constraint programs contain both decision variables (which we can set) and stochastic variables…

Artificial Intelligence · Computer Science 2009-03-09 Toby Walsh

Marginal effects analysis is fundamental to interpreting statistical models, yet existing implementations face computational constraints that limit analysis at scale. We introduce two Julia packages that address this gap. Margins.jl…

Computation · Statistics 2026-01-13 Eric Feltham

Agent based modelling is a simulation method in which autonomous agents interact with their environment and one another, given a predefined set of rules. It is an integral method for modelling and simulating complex systems, such as…

Multiagent Systems · Computer Science 2022-01-10 George Datseris , Ali R. Vahdati , Timothy C. DuBois

PowerSimulations.jl is a Julia-based BSD-licensed power system operations simulation tool developed as a flexible and open source software for quasi-static power systems simulations including Production Cost Models. PowerSimulations.jl…

Systems and Control · Electrical Eng. & Systems 2024-04-05 Jose Daniel Lara , Clayton Barrows , Daniel Thom , Sourabh Dalvi , Duncan S. Callaway , Dheepak Krishnamurthy

The importance of computers is continually increasing in radiotherapy. Efficient algorithms, implementations and the ability to leverage advancements in computer science are crucial to improve cancer care even further and deliver the best…

Medical Physics · Physics 2024-07-08 Renato Bellotti , Antony J. Lomax , Andreas Adelmann , Jan Hrbacek

BlockSystems.jl and NetworkDynamics.jl are two novel software packages which facilitate highly efficient transient stability simulations of power networks. Users may specify inputs and power system design in a convenient modular and…

Systems and Control · Electrical Eng. & Systems 2022-06-14 Anna Büttner , Hans Würfel , Anton Plietzsch , Michael Lindner , Frank Hellmann

The hierarchical equations of motion (HEOM) approach can describe the reduced dynamics of a system simultaneously coupled to multiple bosonic and fermionic environments. The complexity of exactly describing the system-environment…

Increasing emphasis on data and quantitative methods in the biomedical sciences is making biological research more computational. Collecting, curating, processing, and analysing large genomic and imaging data sets poses major computational…

Quantitative Methods · Quantitative Biology 2021-09-22 Elisabeth Roesch , Joe G. Greener , Adam L. MacLean , Huda Nassar , Christopher Rackauckas , Timothy E. Holy , Michael P. H. Stumpf