Christopher Rackauckas

1. A Differentiable Programming System to Bridge Machine Learning and Scientific Computing
   2019/07/17 by Mike Innes, Innes, Mike, Alan Edelman +12 · 2 voices · 13 citations
   Computer Science · #Neural Networks and Applications
2. Universal Differential Equations for Scientific Machine Learning
   2020/01/13 by Christopher Rackauckas, Rackauckas, Christopher, Yingbo Ma +17 · 4 voices · 47 citations
   Biochemistry, Genetics and Molecular Biology · Mathematics · Physics and Astronomy · #Gene Regulatory Network Analysis #Mathematical Biology Tumor Growth #Model Reduction and Neural Networks #cs.LG #math.DS #q-bio.QM #stat.ML
3. NonlinearSolve.jl: High-Performance and Robust Solvers for Systems of Nonlinear Equations in Julia
   2024/03/25 by Avik Pal, Pal, Avik, Flemming Holtorf +20 · 3 voices · 5 citations
   Computer Science · Physics and Astronomy · #Parallel Computing and Optimization Techniques #Polynomial and algebraic computation #Quantum chaos and dynamical systems #math.NA
4. C codegen considered unnecessary: go directly to binary, do not pass C. Compilation of Julia code for deployment in model-based engineering
   2025/02/03 by Fredrik Bagge Carlson, Cody Tapscott, Carlson, Fredrik Bagge +6 · 5 voices · 2 citations
   Computer Science · Decision Sciences · #Model-Driven Software Engineering Techniques #Simulation Techniques and Applications #Modeling and Simulation Systems
5. Automated translation and accelerated solving of differential equations on multiple GPU platforms
   2023/04/13 by Utkarsh Utkarsh, Valentin Churavy, Yingbo Ma +9 · 3 voices · 4 citations
   Computer Science · #Advanced Data Storage Technologies #Distributed and Parallel Computing Systems #Parallel Computing and Optimization Techniques
6. Automatic Differentiation of Programs with Discrete Randomness
   2022/10/16 by Gaurav Arya, Arya, Gaurav, Moritz Schauer +6 · 2 voices · 5 citations
   Computer Science · Decision Sciences · #cs.LG #cs.MS #math.NA #math.PR
7. Differentiable Programming for Differential Equations: A Review
   2024/06/14 by Facundo Sapienza, Sapienza, Facundo, Jordi Bolíbar +19 · 7 citations
   Computer Science · Mathematics · Engineering · #Optimization and Variational Analysis #Advanced Optimization Algorithms Research #Optimization and Mathematical Programming
8. Stiff neural ordinary differential equations
   2021/09/01 by Suyong Kim, Weiqi Ji, Sili Deng +2 · 3 citations
   Computer Science · Mathematics · Physics and Astronomy · #Model Reduction and Neural Networks #Neural Networks and Reservoir Computing #Numerical methods for differential equations
9. A Comparison of Automatic Differentiation and Continuous Sensitivity Analysis for Derivatives of Differential Equation Solutions
   2018/12/05 by Yingbo Ma, Vaibhav Dixit, Ma, Yingbo +7 · 2 citations
   Computer Science · Physics and Astronomy · #FOS: Mathematics #Machine Learning and ELM #Matrix Theory and Algorithms #Model Reduction and Neural Networks #Numerical Analysis (math.NA)
10. Physics-Constrained Flow Matching: Sampling Generative Models with Hard Constraints
    2025/06/04 by Utkarsh Utkarsh, Utkarsh, Utkarsh, Pengfei Cai +7 · 11 citations
    Physics and Astronomy · Computer Science · Materials Science · #Model Reduction and Neural Networks #Generative Adversarial Networks and Image Synthesis #Machine Learning in Materials Science
11. A Fully Adaptive Radau Method for the Efficient Solution of Stiff Ordinary Differential Equations at Low Tolerances
    2024/12/18 by Shreyas Ekanathan, Oscar Smith, Ekanathan, Shreyas +3 · 2 voices · 1 citation
    Mathematics · Computer Science · #Numerical methods for differential equations #Matrix Theory and Algorithms #Differential Equations and Numerical Methods
12. Accelerating Simulation of Stiff Nonlinear Systems using Continuous-Time Echo State Networks
    2020/10/07 by Ranjan Anantharaman, Yingbo Ma, Anantharaman, Ranjan +11 · 1 citation
    Computer Science · Physics and Astronomy · #Dynamical Systems (math.DS) #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Model Reduction and Neural Networks #Neural Networks and Applications #Neural Networks and Reservoir Computing
13. Julia for Biologists
    2021/09/21 by Elisabeth Roesch, Roesch, Elisabeth, Joe G. Greener +11 · 1 voice · 1 citation
    Biochemistry, Genetics and Molecular Biology · #FOS: Biological sciences #Quantitative Methods (q-bio.QM) #q-bio.QM
14. Composing Modeling and Simulation with Machine Learning in Julia
    2021/05/12 by Christopher Rackauckas, Ranjan Anantharaman, Rackauckas, Chris +23 · 1 citation
    Computer Science · Physics and Astronomy · Engineering · #Neural Networks and Reservoir Computing #Model Reduction and Neural Networks #Optical Network Technologies
15. Scalable higher-order nonlinear solvers via higher-order automatic differentiation
    2025/01/28 by Songchen Tan, Tan, Songchen, Keming Miao +5 · 1 voice · 1 citation
    Engineering · Mathematics · #Control Systems and Identification #Advanced Optimization Algorithms Research #Advanced Adaptive Filtering Techniques