Publications

Some New Results on the Maximum Growth Factor in Gaussian Elimination
March 2023
Alan Edelman, John Urschel
Locally Regularized Neural Differential Equations: Some Black Boxes Were Meant to Remain Closed!
March 2023
Avik Pal, Alan Edelman, Chris Rackauckas
Stably Accelerating Stiff Quantitative Systems Pharmacology Models: Continuous-Time Echo State Networks as Implicit Machine Learning
February 2023
Ranjan Anantharaman, Anas Abdelrehim, Anand Jain, Avik Pal, Danny Sharp, Utkarsh, Alan Edelman, Chris Rackauckas
Differentiable Modeling to Unify Machine Learning and Physical Models and Advance Geosciences
January 2023
Chaopeng Shen, Alison P. Appling, Pierre Gentine, Toshiyuki Bandai, Hoshin Gupta, Alexandre Tartakovsky, Marco Baity-Jesi, Fabrizio Fenicia, Daniel Kifer, Li Li, Xiaofeng Liu, Wei Ren, Yi Zheng, Ciaran J. Harman, Martyn Clark, Matthew Farthing, Dapeng Feng, Praveen Kumar, Doaa Aboelyazeed, Farshid Rahmani, Hylke E. Beck, Tadd Bindas, Dipankar Dwivedi, Kuai Fang, Marvin Höge, Chris Rackauckas, Tirthankar Roy, Chonggang Xu, Kathryn Lawson
AutoMat: Automated Materials Discovery for Electrochemical Systems
December 2022
Emil Annevelink, Rachel Kurchin, Eric Muckley, Lance Kavalsky, Vinay I. Hegde, Valentin Sulzer, Shang Zhu, Jiankun Pu, David Farina, Matthew Johnson, Dhairya Gandhi, Adarsh Dave, Hongyi Lin, Alan Edelman, Bharath Ramsundar, James Saal, Christopher Rackauckas, Viral Shah, Bryce Meredig & Venkatasubramanian Viswanathan
Continuous-Time Echo State Networks for Predicting Power System Dynamics
November 2022
Ciaran Roberts, José Daniel Lara, Rodrigo Henriquez-Auba, Matthew Bossart, Ranjan Anantharaman, Chris Rackauckas, Bri-Mathias Hodge, Duncan S. Callaway
A Differentiable Ecosystem Modeling Framework for Large-scale Inverse Problems: Demonstration with Photosynthesis Simulations
November 2022
Doaa Aboelyazeed, Chonggang Xu, Forrest M. Hoffman, Alex W. Jones, Chris Rackauckas, Kathryn E. Lawson, and Chaopeng Shen
Stochastic Optimal Control via Local Occupation Measures
November 2022
Flemming Holtorf, Christopher Rackauckas
Model-Form Epistemic Uncertainty Quantification for Modeling with Differential Equations: Application to Epidemiology.
October 2022
Erin Acquesta, Teresa Portone, Raj Dandekar, Chris Rackauckas, Rileigh Bandy, Jose Huerta, Dytzel, India
Capturing Missing Physics in Climate Model Parameterizations Using Neural Differential Equations
October 2022
Ali Ramadhan, John C Marshall, Andre Nogueira Souza, Xin Kai Lee, Ulyana Piterbarg, Adeline Hillier, Gregory LeClaire Wagner, Christopher Rackauckas, Chris Hill, Jean-Michel Campin, Raffaele Ferrari
Automatic Differentiation of Programs with Discrete Randomness
October 2022
Gaurav Arya, Moritz Schauer, Frank Schäfer, Chris Rackauckas
Constrained Smoothers for State Estimation of Vapor Compression Cycles
September 2022
Vedang M. Deshpande, Christopher R. Laughman, Yingbo Ma, Chris Rackauckas
DelayDiffEq: Generating Delay Differential Equation Solvers via Recursive Embedding of Ordinary Differential Equation Solvers
August 2022
David Widmann, Chris Rackauckas
GlobalSensitivity.jl: Performant and Parallel Global Sensitivity Analysis with Julia
August 2022
Vaibhav Kumar Dixit, Christopher Rackauckas
Catalyst: Fast Biochemical Modeling with Julia
August 2022
Torkel E. Loman, Yingbo Ma, Vasily Ilin, Shashi Gowda, Niklas Korsbo, Nikhil Yewale, Chris Rackauckas, Samuel A. Isaacson
Parallelizing Explicit and Implicit Extrapolation Methods for Ordinary Differential Equations
July 2022
Utkarsh, Chris Elrod, Yingbo Ma, Christopher Rackauckas
Differential Methods for Assessing Sensitivity in Biological Models
June 2022
Rachel Mester, Alfonso Landeros, Chris Rackauckas, Kenneth Lange
Plots.jl -- A User Extendable Plotting API for the Julia Programming Language
April 2022
Simon Christ, Daniel Schwabeneder, Christopher Rackauckas
ReservoirComputing.jl: An Efficient and Modular Library for Reservoir Computing Models
April 2022
Francesco Martinuzzi, Chris Rackauckas, Anas Abdelrehim, Miguel D. Mahecha, Karin Mora
Accelerating Advances in Landscape Connectivity Modeling with the ConScape Library
April 2022
Bram Van Moorter, Ilkka Kivimäki, Andreas Noack, Robin Devooght, Manuela Panzacchi, Kimberly R. Hall, Pierre Leleux, Marco Saerens
Mixing Implicit and Explicit Deep Learning with Skip DEQs and Infinite Time Neural ODEs (Continuous DEQs)
February 2022
Avik Pal, Alan Edelman, Christopher Rackauckas
Symbolic-Numeric Integration of Univariate Expressions Based on Sparse Regression
February 2022
Shahriar Iravanian, Carl Julius Martensen, Alessandro Cheli, Shashi Gowda, Anand Jain, Yingbo Ma, Chris Rackauckas
Two Heads Are Better Than One: Current Landscape of Integrating QSP and Machine Learning
February 2022
Tongli Zhang, Ioannis P. Androulakis, Peter Bonate, Limei Cheng, Tomáš Helikar, Jaimit Parikh, Christopher Rackauckas, Kalyanasundaram Subramanian & Carolyn R. Cho
Composable and Reusable Neural Surrogates to Predict System Response of Causal Model Components
January 2022
Ranjan Anantharaman, Anas Abdelrehim, Francesco Martinuzzi, Sharan Yalburgi, Elliot Saba, Keno Fischer, Glen Hertz, Pepijn de Vos, Chris Laughman, Yingbo Ma, Viral Shah, Alan Edelman, Chris Rackauckas
Automated Code Optimization with E-Graphs
December 2021
Alessandro Cheli, Christopher Rackauckas
Differentiable State Space Models and Hamiltonian Monte Carlo Estimation
December 2021
David Childers, Jesus Fernandez-Villaverde, Jesse Perla, Cameron Pfiffer, Christopher Rackauckas, Peifan Wu
A Comparison of Automatic Differentiation and Continuous Sensitivity Analysis for Derivatives of Differential Equation Solutions
December 2021
Yingbo Ma, Vaibhav Dixit, Michael J Innes, Xingjian Guo, Chris Rackauckas
Data-Efficient Training with Physics-Enhanced Deep Surrogates
November 2021
Raphael Pestourie, Youssef Mroueh, Chris Rackauckas, Payel Das, Steven G. Johnson
Platooning for Improved Safety and Efficiency of Semi-Trucks (PISES–III)
November 2021
Venkatasubramanian Viswanathan, Varun Shankar, Gavin D Portwood, Arvind T Mohan, Peetak P Mitra, Dilip Krishnamurthy, Christopher Rackauckas, Lucas A Wilson, David P Schmidt
Generalized Physics-Informed Learning Through Language-Wide Differentiable Programming
November 2021
Christopher Rackauckas, Alan Edelman, Keno Fischer, Mike Innes, Elliot Saba, Viral B Shah, Will Tebbutt
Physics-Enhanced Deep Surrogates for PDEs
November 2021
Raphaël Pestourie, Youssef Mroueh, Chris Rackauckas, Payel Das, Steven G. Johnson
Differential Methods for Assessing Sensitivity in Biological Models
November 2021
Mester R, Landeros A, Rackauckas C, Lange K
Stably Accelerating Stiff Quantitative Systems Pharmacology Models: Continuous-Time Echo State Networks as Implicit Machine Learning
October 2021
Ranjan Anantharaman, Anas Abdelrehim, Anand Jain, Avik Pal, Danny Sharp, Utkarsh Utkarsh, Christopher Vincent Rackauckas
Validation and Parameterization of a Novel Physics-Constrained Neural Dynamics Model Applied to Turbulent Fluid Flow
October 2021
Varun Shankar, Gavin D. Portwood, Arvind T. Mohan, Peetak P. Mitra, Dilip Krishnamurthy, Christopher Rackauckas, Lucas A. Wilson, David P. Schmidt, and Venkatasubramanian Viswanathan
Hybrid Mechanistic + Neural Model of Laboratory Helicopter
September 2021
Christopher Rackauckas, Roshan Sharma, Bernt Lie
Julia for Biologists
September 2021
Elisabeth Roesch, Joe G Greener, Adam L MacLean, Huda Nassar, Christopher Rackauckas, Timothy E Holy, Michael PH Stumpf
AbstractDifferentiation. jl: Backend-Agnostic Differentiable Programming in Julia
September 2021
Frank Schäfer, Mohamed Tarek, Lyndon White, Chris Rackauckas
Collocation Based Training of Neural Ordinary Differential Equations
July 2021
Elisabeth Roesch, Christopher Rackauckas, Michael PH Stumpf
NeuralPDE: Automating Physics-Informed Neural Networks (PINNs) with Error Approximations
July 2021
Kirill Zubov, Zoe McCarthy, Yingbo Ma, Francesco Calisto, Valerio Pagliarino, Simone Azeglio, Luca Bottero, Emmanuel Luján, Valentin Sulzer, Ashutosh Bharambe, Nand Vinchhi, Kaushik Balakrishnan, Devesh Upadhyay, Chris Rackauckas
A Campus Simulation Model Supporting the Safe Blues Experiment
May 2021
Thomas Graham, Azam Asanjarani, Shane G. Henderson, Yoni Nazarathy, Keng Chew, Marijn Jansen, Christopher Rackauckas, Kirsty Short, Peter G Taylor, Aapeli Vuorinen, Ilze Ziedins
High-Performance Symbolic-Numerics via Multiple Dispatch
May 2021
Shashi Gowda, Yingbo Ma, Alessandro Cheli, Maja Gwozdz, Viral B. Shah, Alan Edelman, Christopher Rackauckas
Opening the Blackbox: Accelerating Neural Differential Equations by Regularizing Internal Solver Heuristics
May 2021
Avik Pal, Yingbo Ma, Viral Shah, Christopher Rackauckas
Composing Modeling and Simulation with Machine Learning in Julia
May 2021
Chris Rackauckas, Ranjan Anantharaman, Alan Edelman, Shashi Gowda, Maja Gwozdz, Anand Jain, Chris Laughman, Yingbo Ma, Francesco Martinuzzi, Avik Pal, Utkarsh Rajput, Elliot Saba, Viral B. Shah
Accelerating Simulation of Stiff Nonlinear Systems Using Continuous-Time Echo State Networks
March 2021
Ranjan Anantharaman, Yingbo Ma, Shashi Gowda, Chris Laughman, Viral Shah, Alan Edelman, Chris Rackauckas
ModelingToolkit: A Composable Graph Transformation System For Equation-Based Modeling
March 2021
Yingbo Ma, Shashi Gowda, Ranjan Anantharaman, Chris Laughman, Viral Shah, Chris Rackauckas
Stiff Neural Ordinary Differential Equations
March 2021
Suyong Kim, Weiqi Ji, Sili Deng, Christopher Rackauckas
Circuitscape in Julia: Empowering Dynamic Approaches to Connectivity Assessment
March 2021
Kimberly R. Hall, Ranjan Anantharaman, Vincent A. Landau, Melissa Clark, Brett G. Dickson, Aaron Jones, Jim Platt, Alan Edelman and Viral B. Shah
Safe Blues: The Case for Virtual Safe Virus Spread in the Long-Term Fight Against Epidemics
March 2021
Raj Dandekar, Shane G. Henderson, Hermanus M. Jansen, Joshua McDonald, Sarat Moka, Yoni Nazarathy, Christopher Rackauckas, Peter G. Taylor, Aapeli Vuorinen
Forecasting Virus Outbreaks With Social Media Data via Neural Ordinary Differential Equations
January 2021
Matías Núñez, Nadia L. Barreiro, Rafael A. Barrio, Christopher Rackauckas
Efficient Precision Dosing Under Estimated Uncertainties via Koopman Expectations of Bayesian Posteriors with Pumas
January 2021
Chris Rackauckas, Vaibhav Dixit, Adam R. Gerlach, Vijay Ivaturi
Omniscape.jl: Software to Compute Omnidirectional Landscape Connectivity
January 2021
Vincent A. Landau, Viral B. Shah, Ranjan Anantharaman, Kimberly R. Hall4
Implications of Delayed Reopening in Controlling the COVID-19 Surge in Southern and West-Central USA
December 2020
Raj Dandekar, Emma Wang, George Barbastathis, Chris Rackauckas
Learning Non-Linear Spatio-Temporal Dynamics with Convolutional Neural ODEs
December 2020
Varun Shankar, Gavin D. Portwood, Arvind T. Mohan, Peetak P. Mitra, Christopher Rackauckas, Lucas A. Wilson, David P. Schmidt, Venkatasubramanian Viswanathan
Bayesian Neural Ordinary Differential Equations
December 2020
Raj Dandekar, Karen Chung, Vaibhav Dixit, Mohamed Tarek, Aslan Garcia-Valadez, Krishna Vishal Vemula, Chris Rackauckas
ACED: Accelerated Computational Electrochemical Systems Discovery
November 2020
Rachel C. Kurchin, Eric Muckley, Lance Kavalsky, Vinay Hegde, Dhairya Gandhi, Xiaoyu Sun, Matthew Johnson, Alan Edelman, James Saal, Christopher Vincent Rackauckas, Bryce Meredig, Viral Shah, Venkatasubramanian Viswanathan
Accelerated Predictive Healthcare Analytics with Pumas, a High Performance Pharmaceutical Modeling and Simulation Platform
November 2020
Chris Rackauckas, Yingbo Ma, Andreas Noack, Vaibhav Dixit, Patrick Kofod Mogensen, Simon Byrne, Shubham Maddhashiya, José Bayoán Santiago Calderón, Joakim Nyberg, Jogarao V.S. Gobburu, Vijay Ivaturi
Capturing Missing Physics in Climate Model Parameterizations Using Neural Differential Equations
October 2020
Ali Ramadhan, John Marshall, Andre Souza, Gregory LeClaire Wagner, Manvitha Ponnapati, Christopher Rackauckas
World Age in Julia: Optimizing Method Dispatch in the Presence of Eval (Extended Version)
October 2020
Julia Belyakova, Benjamin Chung, Jack Gelinas, Jameson Nash, Ross Tate, Jan Vitek
Uncertainty Quantification of Ocean Parameterizations: Application to the K-Profile-Parameterization for Penetrative Convection
October 2020
Andre Nogueira Souza, Gregory LeClaire Wagner, Ali Ramadhan, Valentin Churavy, Brandon Allen, James Schloss, Jean-Michel Campin, Chris Hill, Alan Edelman, John Marshall, Glenn R. Flierl, Raffaele Ferrari
Beyond Deterministic Models in Drug Discovery and Development
October 2020
Itziar Irurzun-Arana, Christopher Rackauckas, Thomas O McDonald, Iñaki F Trocóniz
Oceananigans.jl: Fast and Friendly Geophysical Fluid Dynamics on GPUs
September 2020
Ali Ramadhan, Gregory LeClaire Wagner, Chris Hill, Jean-Michel Campin, Valentin Churavy, Tim Besard, Andre Souza, Alan Edelman, Raffaele Ferrari, John Marshall
Hybrid Mechanistic + Neural Model of Laboratory Helicopter
September 2020
Christopher Rackauckas, Roshan Sharma, Bernt Lie
The Koopman Expectation: An Operator Theoretic Method for Efficient Analysis and Optimization of Uncertain Hybrid Dynamical Systems
August 2020
Adam R. Gerlach, Andrew Leonard, Jonathan Rogers, Chris Rackauckas
Interoperating Deep Learning Models with ONNX.jl
August 2020
Ayush Shridhar, Phil Tomson, Mike Innes
Signal Enhancement for Magnetic Navigation Challenge Problem
July 2020
Albert R. Gnadt, Joseph Belarge, Aaron Canciani, Lauren Conger, Joseph Curro, Alan Edelman, Peter Morales, Michael F. O'Keeffe, Jonathan Taylor, Christopher Rackauckas
StochasticDelayDiffEq.jl - An Integrator Interface for Stochastic Delay Differential Equations in Julia
July 2020
Henrik T Sykora, Christopher V. Rackauckas, David Widmann, Daniel Bachrathy
A Machine Learning Aided Global Diagnostic and Comparative Tool to Assess Effect of Quarantine Control in Covid-19 Spread
July 2020
Raj Dandekar, Chris Rackauckas, George Barbastathis
A Multi-Control Climate Policy Process for a Trusted Decision Maker
May 2020
Henri F. Drake , Ronald L. Rivest, John Deutch, Alan Edelman
Safe Blues: A Method for Estimation and Control in the Fight Against COVID-19
May 2020
Raj Dandekar, Shane G. Henderson, Marijn Jansen, Sarat Moka, Yoni Nazarathy, Christopher Rackauckas, Peter G. Taylor, Aapeli Vuorinen
Sense & Sensitivities: the Path to General-Purpose Algorithmic Differentiation
March 2020
Michael J Innes
Generalized Physics-Informed Learning Through Language-Wide Differentiable Programming
March 2020
Chris Rackauckas, Alan Edelman, Keno Fischer, Mike Innes, Elliot Saba, Viral B. Shah, Will Tebbutt
WordTokenizers.jl: Basic Tools for Tokenizing Natural Language in Julia
February 2020
Ayush Kaushal, Lyndon White, Mike Innes, Rohit Kumar
Universal Differential Equations for Scientific Machine Learning
January 2020
Christopher Rackauckas, Yingbo Ma, Julius Martensen, Collin Warner, Kirill Zubov, Rohit Supekar, Dominic Skinner, Ali Ramadhan, Alan Edelman
Basic Threading Examples in JuliaLang v1.3
Dec 2019
Jameson Nash, Jeff Bezanson and Kiran Pamnany
Highly-Scalable, Physics-Informed GANs for Learning Solutions of Stochastic PDEs
October 2019
Liu Yang, Sean Treichler, Thorsten Kurth, Keno Fischer, David Barajas-Solano, Josh Romero, Valentin Churavy, Alexandre Tartakovsky, Michael Houston, Prabhat, George Karniadakis
Sparsity Programming: Automated Sparsity-Aware Optimizations in Differentiable Programming
September 2019
Shashi Gowda, Yingbo Ma, Valentin Churavy, Alan Edelman, Christopher Rackauckas
Differentiation of High-Level Language Semantics
September 2019
Michael Innes
A Differentiable Programming System to Bridge Machine Learning and Scientific Computing
July 2019
Mike Innes, Alan Edelman, Keno Fischer, Chris Rackauckas, Elliot Saba, Viral B Shah, Will Tebbutt
Rapid Software Prototyping for Heterogeneous and Distributed Platforms
June 2019
Tim Besard, Valentin Churavy, Alan Edelman, Bjorn De Sutter
Julia e Flux: Modernizando o Aprendizado de Máquina
Dec 2019
Dhairya Gandhi, Mike Innes, Elliot Saba, Keno Fischer, Viral Shah
Julia: A Fresh Approach to Technical Computing and Data Processing
March 2019
Alan Edelman
DiffEqFlux.jl - A Julia Library for Neural Differential Equations
Feburary 2019
Chris Rackauckas, Mike Innes, Yingbo Ma, Jesse Bettencourt, Lyndon White, Vaibhav Dixit
Circuitscape in Julia: High Performance Connectivity Modelling to Support Conservation Decisions
January 2019
Ranjan Anantharaman, Kimberly Hall, Viral Shah, Alan Edelman
Cataloging the Visible Universe through Bayesian Inference in Julia at Petascale
January 2019
Jeffrey Regier, Keno Fischer, Kiran Pamnany, Andreas Noack, Jarrett Revels, Maximilian Lam, Steve Howard, Ryan Giordano, David Schlegel, Jon McAuliffe, Rollin Thomas, Prabhat
A Comparison of Automatic Differentiation and Continuous Sensitivity Analysis for Derivatives of Differential Equation Solutions
December 2018
Christopher Rackauckas, Yingbo Ma, Vaibhav Dixit, Xingjian Guo, Mike Innes, Jarrett Revels, Joakim Nyberg, Vijay Ivaturi
Circuit-Theory Applications to Connectivity Science and Conservation
November 2018
Brett G Dickson, Christine M Albano, Ranjan Anantharaman, Paul Beier, Joe Fargione, Tabitha A Graves, Miranda E Gray, Kimberly R Hall, Josh J Lawler, Paul B Leonard, Caitlin E Littlefield, Meredith L McClure, John Novembre, Carrie A Schloss, Nathan H Schumaker, Viral B Shah, David M Theobald
Fashionable Modelling with Flux
November 2018
Michael J Innes, Elliot Saba, Keno Fischer, Dhairya Gandhi, Marco Concetto Rudilosso, Neethu Mariya Joy, Tejan Karmali, Avik Pal and Viral Shah
Julia: Dynamism and Performance Reconciled by Design
November 2018
Jeff Bezanson, Jiahao Chen, Benjamin Chung, Stefan Karpinski, Viral B. Shah, Jan Vitek and Lionel Zoubritzky
Julia Subtyping: A Rational Reconstruction
November 2018
Francesco Zappa Nardelli, Julia Belyakova, Artem Pelenitsyn, Benjamin Chung, Jeff Bezanson and Jan Vitek
Automatic Full Compilation of Julia Programs and ML Models to Cloud TPUs
October 2018
Keno Fischer and Elliot Saba
Interdisciplinary Case Study: How Mathematicians and Biologists Found Order in Cellular Noise
October 2018
Christopher Rackauckas, Thomas Schilling, Qing Nie
Don't Unroll Adjoint: Differentiating SSA-Form Programs
October 2018
Michael J Innes
Fast Flexible Function Dispatch in Julia
August 2018
Jeff Bezanson, Jake Bolewski, Jiahao Chen
Fast Computation of the Principal Components of Genotype Matrices in Julia
August 2018
Jiahao Chen, Andreas Noack, Alan Edelman
Confederated Modular Differential Equation APIs for Accelerated Algorithm Development and Benchmarking
July 2018
Christopher Rackauckas, Qing Nie
Flux: Elegant Machine Learning with Julia
May 2018
Mike Innes
Mean-Independent Noise Control of Cell Fates via Intermediate States
May 2018
Christopher Rackauckas, Thomas Schilling, Qing Nie
Stability-Optimized High Order Methods and Stiffness Detection for Pathwise Stiff Stochastic Differential Equations
April 2018
Christopher Rackauckas, Qing Nie
On Machine Learning and Programming Languages
February 2018
Mike Innes, Stefan Karpinski, Viral Shah, James Bradbury, David Barber, Pontus Stenetorp, Valentin Churavy, Simon Danisch, Alan Edelman, Jon Malmaud, Jarrett Revels, Tim Besard, Deniz Yuret
A More Open Efficient Future for AI Development and Data Science with an Introduction to Julia
December 2017
Alan Edelman
DifferentialEquations.jl – A Performant and Feature-Rich Ecosystem for Solving Differential Equations in Julia
May 2017
Christopher Rackauckas , Qing Nie
Julia: A Fresh Approach to Numerical Computing
February 2017
Jeff Bezanson, Alan Edelman, Stefan Karpinski and Viral B. Shah
Accelerated Convolutions for Efficient Multi-Scale Time to Contact Computation in Julia
December 2016
Alexander Amini, Berthold Horn, Alan Edelman
Vive La Difference!
November 2016
Peter Farley, Michael Aichinger, Andreas Binder, Steve Wilcockson, Viral Shah, Simon Byrne, Sachvir Cheema, James Church
GFLOW: Software for Modelling Circuit Theory-Based Connectivity at any Scale
November 2016
Paul B. Leonard, Edward B. Duffy, Robert F. Baldwin, Brad H. McRae, Viral B. Shah, Tanmay K. Mohapatra
Julia Implementation of the Dynamic Distributed Dimensional Data Model
August 2016
Alexander Chen, Alan Edelman, Jeremy Kepner, Vijay Gadepally, Dylan Hutchison
Circuitscape: Modeling Landscape Connectivity to Promote Conservation and Human Health
May 2016
Brad McRae, Viral B. Shah
Julia Introduction
October 2015
Alan Edelman
Parallel Prefix Polymorphism Permits Parallelization, Presentation & Proof
November 2014
Jiahao Chen and Alan Edelman
Array Operators Using Multiple Dispatch: A Design Methodology for Array Implementations in Dynamic Languages
February 2014
Jeff Bezanson, Jiahao Chen, Stefan Karpinski, Viral Shah and Alan Edelman
Novel Algebras for Advanced Analytics in Julia
November 2013
Viral B. Shah, Alan Edelman, Stefan Karpinski, Jeff Bezanson, Jeremy Kepner
Julia: A Fast Dynamic Language for Technical Computing
September 2012
Jeff Bezanson, Stefan Karpinski, Viral B. Shah, Alan Edelman