Confederated modular differential equation APIs for accelerated algorithm development and benchmarking. - Christopher Rackauckas; Qing Nie (Adv. Eng. Softw., 2019)

DiffEqFlux.jl - A Julia Library for Neural Differential Equations. - Christopher Rackauckas; Mike Innes; Yingbo Ma; Jesse Bettencourt; Lyndon White; Vaibhav Dixit (CoRR, 2019)

A Differentiable Programming System to Bridge Machine Learning and Scientific Computing. - Mike Innes; Alan Edelman; Keno Fischer; Christopher Rackauckas; Elliot Saba; Viral B. Shah; Will Tebbutt (CoRR, 2019)

Generalized Physics-Informed Learning through Language-Wide Differentiable Programming. - Christopher Rackauckas; Alan Edelman; Keno Fischer; Mike Innes; Elliot Saba; Viral B. Shah; Will Tebbutt (AAAI Spring Symposium: MLPS, 2020)

Stability-Optimized High Order Methods and Stiffness Detection for Pathwise Stiff Stochastic Differential Equations. - Christopher Rackauckas; Qing Nie (HPEC, 2020)

Universal Differential Equations for Scientific Machine Learning. - Christopher Rackauckas; Yingbo Ma; Julius Martensen; Collin Warner; Kirill Zubov; Rohit Supekar; Dominic Skinner; Ali Jasim Ramadhan (CoRR, 2020)

Signal Enhancement for Magnetic Navigation Challenge Problem. - Albert R. Gnadt; Joseph Belarge; Aaron Canciani; Lauren Conger; Joseph Curro; Alan Edelman; Peter Morales; Michael F. O'Keeffe; Jonathan Taylor; Christopher Rackauckas (CoRR, 2020)

ACED: Accelerated Computational Electrochemical systems Discovery. - Rachel C. Kurchin; Eric Muckley; Lance Kavalsky; Vinay I. Hegde; Dhairya Gandhi; Xiaoyu Sun; Matthew Johnson; Alan Edelman; James E. Saal; Christopher Vincent Rackauckas; Bryce Meredig; Viral B. Shah; et al. (CoRR, 2020)

Bayesian Neural Ordinary Differential Equations. - Raj Dandekar; Vaibhav Dixit; Mohamed Tarek; Aslan Garcia-Valadez; Christopher Rackauckas (CoRR, 2020)

A Machine Learning-Aided Global Diagnostic and Comparative Tool to Assess Effect of Quarantine Control in COVID-19 Spread. - Raj Dandekar; Christopher Rackauckas; George Barbastathis (Patterns, 2020)

Accelerating Simulation of Stiff Nonlinear Systems using Continuous-Time Echo State Networks. - Ranjan Anantharaman; Yingbo Ma; Shashi Gowda; Chris Laughman; Viral B. Shah; Alan Edelman; Christopher Rackauckas (AAAI Spring Symposium: MLPS, 2021)

A Comparison of Automatic Differentiation and Continuous Sensitivity Analysis for Derivatives of Differential Equation Solutions. - Yingbo Ma; Vaibhav Dixit; Michael J. Innes; Xingjian Guo; Christopher Rackauckas (HPEC, 2021)

Opening the Blackbox: Accelerating Neural Differential Equations by Regularizing Internal Solver Heuristics. - Avik Pal; Yingbo Ma; Viral B. Shah; Christopher Vincent Rackauckas (ICML, 2021)

High-performance symbolic-numerics via multiple dispatch. - Shashi Gowda; Yingbo Ma; Alessandro Cheli; Maja Gwózdz; Viral B. Shah; Alan Edelman; Christopher Rackauckas (ACM Commun. Comput. Algebra, 2021)

ModelingToolkit: A Composable Graph Transformation System For Equation-Based Modeling. - Yingbo Ma; Shashi Gowda; Ranjan Anantharaman; Chris Laughman; Viral B. Shah; Christopher Rackauckas (CoRR, 2021)

Stiff Neural Ordinary Differential Equations. - Suyong Kim; Weiqi Ji; Sili Deng; Christopher Rackauckas (CoRR, 2021)

NeuralPDE: Automating Physics-Informed Neural Networks (PINNs) with Error Approximations. - Kirill Zubov; Zoe McCarthy; Yingbo Ma; Francesco Calisto; Valerio Pagliarino; Simone Azeglio; Luca Bottero; Emmanuel Luján; Valentin Sulzer; Ashutosh Bharambe; Nand Vinchhi; Kaushik Balakrishnan; et al. (CoRR, 2021)

AbstractDifferentiation.jl: Backend-Agnostic Differentiable Programming in Julia. - Frank Schäfer; Mohamed Tarek; Lyndon White; Christopher Rackauckas (CoRR, 2021)

Physics-enhanced deep surrogates for PDEs. - Raphaël Pestourie; Youssef Mroueh; Chris Rackauckas; Payel Das; Steven G. Johnson (CoRR, 2021)

Automated Code Optimization with E-Graphs. - Alessandro Cheli; Christopher Rackauckas (CoRR, 2021)

Safe Blues: The case for virtual safe virus spread in the long-term fight against epidemics. - Raj Dandekar; Shane G. Henderson; Hermanus M. Jansen; Joshua McDonald; Sarat Babu Moka; Yoni Nazarathy; Christopher Rackauckas; Peter G. Taylor; Aapeli Vuorinen (Patterns, 2021)

Constrained Smoothers for State Estimation of Vapor Compression Cycles. - Vedang M. Deshpande; Christopher R. Laughman; Yingbo Ma; Chris Rackauckas (ACC, 2022)

Composing Modeling And Simulation With Machine Learning In Julia. - Chris Rackauckas; Maja Gwózdz; Anand Jain; Yingbo Ma; Francesco Martinuzzi; Utkarsh Rajput; Elliot Saba; Viral B. Shah; Ranjan Anantharaman; Alan Edelman; Shashi Gowda; Avik Pal; et al. (ANNSIM, 2022)

Parallelizing Explicit and Implicit Extrapolation Methods for Ordinary Differential Equations. - Utkarsh Rajput; Chris Elrod; Yingbo Ma; Konstantin Althaus; Christopher Rackauckas (HPEC, 2022)

Automatic Differentiation of Programs with Discrete Randomness. - Gaurav Arya; Moritz Schauer; Frank Schäfer; Christopher Rackauckas (NeurIPS, 2022)

Symbolic-numeric integration of univariate expressions based on sparse regression. - Shahriar Iravanian; Carl Julius Martensen; Alessandro Cheli; Shashi Gowda; Anand Jain; Yingbo Ma; Chris Rackauckas (ACM Commun. Comput. Algebra, 2022)

Mixing Implicit and Explicit Deep Learning with Skip DEQs and Infinite Time Neural ODEs (Continuous DEQs). - Avik Pal; Alan Edelman; Christopher Rackauckas (CoRR, 2022)

Plots.jl - a user extendable plotting API for the julia programming language. - Simon Christ; Daniel Schwabeneder; Christopher Rackauckas (CoRR, 2022)

Parallelizing Explicit and Implicit Extrapolation Methods for Ordinary Differential Equations. - Utkarsh Rajput; Chris Elrod; Yingbo Ma; Christopher Rackauckas (CoRR, 2022)

DelayDiffEq: Generating Delay Differential Equation Solvers via Recursive Embedding of Ordinary Differential Equation Solvers. - David Widmann; Chris Rackauckas (CoRR, 2022)

Stochastic Optimal Control via Local Occupation Measures. - Flemming Holtorf; Christopher Rackauckas (CoRR, 2022)

ReservoirComputing.jl: An Efficient and Modular Library for Reservoir Computing Models. - Francesco Martinuzzi; Chris Rackauckas; Anas Abdelrehim; Miguel D. Mahecha; Karin Mora (J. Mach. Learn. Res., 2022)

GlobalSensitivity.jl: Performant and Parallel Global Sensitivity Analysis with Julia. - Vaibhav Dixit; Christopher Rackauckas (J. Open Source Softw., 2022)

Differential methods for assessing sensitivity in biological models. - Rachel Mester; Alfonso Landeros; Chris Rackauckas; Kenneth Lange (PLoS Comput. Biol., 2022)

Continuous Deep Equilibrium Models: Training Neural ODEs Faster by Integrating Them to Infinity. - Avik Pal; Alan Edelman; Chris Rackauckas (HPEC, 2023)

Locally Regularized Neural Differential Equations: Some Black Boxes were meant to remain closed! - Avik Pal; Alan Edelman; Christopher Vincent Rackauckas (ICML, 2023)

Sum-of-Squares Bounds for Quantum Optimal Control. - Flemming Holtorf; Frank Schäfer; Julian Arnold; Christopher Rackauckas; Alan Edelman (QCE, 2023)

Differentiable modeling to unify machine learning and physical models and advance Geosciences. - Chaopeng Shen; Alison P. Appling; Pierre Gentine; Toshiyuki Bandai; Hoshin V. Gupta; Alexandre Tartakovsky; Marco Baity-Jesi; Fabrizio Fenicia; Daniel Kifer; Li Li; Xiaofeng Liu; Wei Ren; et al. (CoRR, 2023)

Efficient hybrid modeling and sorption model discovery for non-linear advection-diffusion-sorption systems: A systematic scientific machine learning approach. - Vinícius V. Santana; Erbet Almeida Costa; Carine M. Rebello; Ana M. Ribeiro; Chris Rackauckas; Idelfonso B. R. Nogueira (CoRR, 2023)

Performance Bounds for Quantum Control. - Flemming Holtorf; Frank Schäfer; Julian Arnold; Christopher Rackauckas; Alan Edelman (CoRR, 2023)

A Practitioner's Guide to Bayesian Inference in Pharmacometrics using Pumas. - Mohamed Tarek; Jose Storopoli; Casey B. Davis; Chris Elrod; Julius Krumbiegel; Chris Rackauckas; Vijay Ivaturi (CoRR, 2023)

Automated Translation and Accelerated Solving of Differential Equations on Multiple GPU Platforms. - Utkarsh Rajput; Valentin Churavy; Yingbo Ma; Tim Besard; Tim Gymnich; Adam R. Gerlach; Alan Edelman; Christopher Rackauckas (CoRR, 2023)

Extending JumpProcess.jl for fast point process simulation with time-varying intensities. - Guilherme Augusto Zagatti; Samuel A. Isaacson; Christopher Rackauckas; Vasily Ilin; See-Kiong Ng; Stéphane Bressan (CoRR, 2023)

Differentiating Metropolis-Hastings to Optimize Intractable Densities. - Gaurav Arya; Ruben Seyer; Frank Schäfer; Alexander K. Lew; Mathieu Huot; Vikash K. Mansinghka; Chris Rackauckas; Kartik Chandra; Moritz Schauer (CoRR, 2023)

Catalyst: Fast and flexible modeling of reaction networks. - Torkel E. Loman; Yingbo Ma; Vasily Ilin; Shashi Gowda; Niklas Korsbo; Nikhil Yewale; Chris Rackauckas; Samuel A. Isaacson (PLoS Comput. Biol., 2023)

Physics-enhanced deep surrogates for partial differential equations. - Raphaël Pestourie; Youssef Mroueh; Chris Rackauckas; Payel Das; Steven G. Johnson (Nat. Mac. Intell., 2023)

Hybrid Symbolic-Numeric and Numerically-Assisted Symbolic Integration. - Shahriar Iravanian; Shashi Gowda; Christopher Rackauckas (ISSAC, 2024)

NonlinearSolve.jl: High-Performance and Robust Solvers for Systems of Nonlinear Equations in Julia. - Avik Pal; Flemming Holtorf; Axel Larsson; Torkel E. Loman; Utkarsh Rajput; Frank Schäfer; Qingyu Qu; Alan Edelman; Chris Rackauckas (CoRR, 2024)

Differentiable Programming for Differential Equations: A Review. - Facundo Sapienza; Jordi Bolibar; Frank Schäfer; Brian Groenke; Avik Pal; Victor Boussange; Patrick Heimbach; Giles Hooker; Fernando Pérez; Per-Olof Persson; Christopher Rackauckas (CoRR, 2024)

A Fully Adaptive Radau Method for the Efficient Solution of Stiff Ordinary Differential Equations at Low Tolerances. - Shreyas Ekanathan; Oscar Smith; Christopher Rackauckas (CoRR, 2024)

SBMLToolkit.jl: a Julia package for importing SBML into the SciML ecosystem. - Paul F. Lang; Anand Jain; Christopher Rackauckas (J. Integr. Bioinform., 2024)

DataInterpolations.jl: Fast Interpolations of 1D data. - Sathvik Bhagavan; Bart de Koning; Shubham Maddhashiya; Christopher Rackauckas (J. Open Source Softw., 2024)

Performance Bounds for Quantum Feedback Control. - Flemming Holtorf; Frank Schäfer; Julian Arnold; Christopher Vincent Rackauckas; Alan Edelman (IEEE Trans. Autom. Control., 2024)

Active Learning Enhanced Surrogate Modeling of Jet Engines in JuliaSim. - Anas Abdelrehim; Dhairya Gandhi; Sharan Yalburgi; Ashutosh Bharambe; Ranjan Anantharaman; Chris Rackauckas (CoRR, 2025)

Scalable higher-order nonlinear solvers via higher-order automatic differentiation. - Songchen Tan; Keming Miao; Alan Edelman; Christopher Rackauckas (CoRR, 2025)

C codegen considered unnecessary: go directly to binary, do not pass C. Compilation of Julia code for deployment in model-based engineering. - Fredrik Bagge Carlson; Cody Tapscott; Gabriel Baraldi; Chris Rackauckas (CoRR, 2025)

Semi-Explicit Neural DAEs: Learning Long-Horizon Dynamical Systems with Algebraic Constraints. - Avik Pal; Alan Edelman; Christopher Rackauckas (CoRR, 2025)

Physics-Constrained Flow Matching: Sampling Generative Models with Hard Constraints. - Utkarsh Utkarsh; Pengfei Cai; Alan Edelman; Rafael Gómez-Bombarelli; Christopher Vincent Rackauckas (CoRR, 2025)

Scientific Machine Learning of Chaotic Systems Discovers Governing Equations for Neural Populations. - Anthony G. Chesebro; David Hofmann; Vaibhav Dixit; Earl K. Miller; Richard H. Granger; Alan Edelman; Christopher Vincent Rackauckas; Lilianne R. Mujica-Parodi; Helmut H. Strey (CoRR, 2025)

Robust parameter estimation for rational ordinary differential equations. - Oren Bassik; Yosef Berman; Soo Go; Hoon Hong; Ilia Ilmer; Alexey Ovchinnikov; Chris Rackauckas; Pedro Soto 001; Chee Yap (Appl. Math. Comput., 2026)