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Blog

Events

Videos

Courses

Case Studies

Data Sheets

White Papers

Publications

Documentation

Publications

Scalable higher-order nonlinear solvers via higher-order automatic differentiation

Chris Rackauckas profile photo

Dr. Chris Rackauckas

Dr. Alan Edelman

Dr. Alan Edelman

A Fully Adaptive Radau Method for the Efficient Solution of Stiff Ordinary Differential Equations at Low Tolerances

Chris Rackauckas profile photo

Dr. Chris Rackauckas

Oscar Smith

Oscar Smith

Differentiable Programming for Differential Equations: A Review

Chris Rackauckas profile photo

Dr. Chris Rackauckas

SBMLToolkit.jl: a Julia package for importing SBML into the SciML ecosystem

Chris Rackauckas profile photo

Dr. Chris Rackauckas

Uncertainty quantified discovery of chemical reaction systems via Bayesian scientific machine learning

Chris Rackauckas profile photo

Dr. Chris Rackauckas

Automated translation and accelerated solving of differential equations on multiple GPU platforms

Chris Rackauckas profile photo

Dr. Chris Rackauckas

Dr. Tim Besard

Dr. Tim Besard

Hydrogen for harvesting the potential of offshore wind: A North Sea case study

Avinash Subramanian profile photo

Dr. Avinash Subramanian

Catalyst: Fast and Flexible Modeling of Reaction Networks

Chris Rackauckas profile photo

Dr. Chris Rackauckas

A Differentiable, Physics-Informed Ecosystem Modeling and Learning Framework for Large-Scale Inverse Problems: Demonstration with Photosynthesis Simulations

Chris Rackauckas profile photo

Dr. Chris Rackauckas

Forecasting Virus Outbreaks with Social Media Data Via Neural Ordinary Differential Equations

Chris Rackauckas profile photo

Dr. Chris Rackauckas

Mapping Out Phase Diagrams with Generative Classifiers

Dr. Alan Edelman

Dr. Alan Edelman

Extending JumpProcess.jl for Fast Point Process Simulation with Time-Varying Intensities

Chris Rackauckas profile photo

Dr. Chris Rackauckas

Differentiating Metropolis-Hastings to Optimize Intractable Densities

Chris Rackauckas profile photo

Dr. Chris Rackauckas

Modular Algorithms for Scientific Computing in Julia

Chris Rackauckas profile photo

Dr. Chris Rackauckas

Neural Jump SDEs (Jump Diffusions) and Neural PDEs

Chris Rackauckas profile photo

Dr. Chris Rackauckas

Finalizing Your Julia Package: Documentation, Testing, Coverage, and Publishing

Chris Rackauckas profile photo

Dr. Chris Rackauckas

How Inexact Models Can Guide Decision Making in Quantitative Systems Pharmacology

Chris Rackauckas profile photo

Dr. Chris Rackauckas

7 Julia Gotchas and How to Handle Them

Chris Rackauckas profile photo

Dr. Chris Rackauckas

Type-Dispatch Design: Post Object-Oriented Programming for Julia

Chris Rackauckas profile photo

Dr. Chris Rackauckas

GPU-Accelerated ODE Solving in R with Julia, the Language of Libraries

Chris Rackauckas profile photo

Dr. Chris Rackauckas

Optimal Number of Workers for Parallel Julia

Chris Rackauckas profile photo

Dr. Chris Rackauckas

Scalable higher-order nonlinear solvers via higher-order automatic differentiation

A Fully Adaptive Radau Method for the Efficient Solution of Stiff Ordinary Differential Equations at Low Tolerances

Differentiable Programming for Differential Equations: A Review

SBMLToolkit.jl: a Julia package for importing SBML into the SciML ecosystem

Uncertainty quantified discovery of chemical reaction systems via Bayesian scientific machine learning

Automated translation and accelerated solving of differential equations on multiple GPU platforms

Hydrogen for harvesting the potential of offshore wind: A North Sea case study

Catalyst: Fast and Flexible Modeling of Reaction Networks

A Differentiable, Physics-Informed Ecosystem Modeling and Learning Framework for Large-Scale Inverse Problems: Demonstration with Photosynthesis Simulations

Forecasting Virus Outbreaks with Social Media Data Via Neural Ordinary Differential Equations

Mapping Out Phase Diagrams with Generative Classifiers

Extending JumpProcess.jl for Fast Point Process Simulation with Time-Varying Intensities

Differentiating Metropolis-Hastings to Optimize Intractable Densities

Modular Algorithms for Scientific Computing in Julia

Neural Jump SDEs (Jump Diffusions) and Neural PDEs

Finalizing Your Julia Package: Documentation, Testing, Coverage, and Publishing

How Inexact Models Can Guide Decision Making in Quantitative Systems Pharmacology

7 Julia Gotchas and How to Handle Them

Type-Dispatch Design: Post Object-Oriented Programming for Julia

GPU-Accelerated ODE Solving in R with Julia, the Language of Libraries

Scalable higher-order nonlinear solvers via higher-order automatic differentiation

A Fully Adaptive Radau Method for the Efficient Solution of Stiff Ordinary Differential Equations at Low Tolerances

Differentiable Programming for Differential Equations: A Review

SBMLToolkit.jl: a Julia package for importing SBML into the SciML ecosystem

Uncertainty quantified discovery of chemical reaction systems via Bayesian scientific machine learning

Automated translation and accelerated solving of differential equations on multiple GPU platforms

Hydrogen for harvesting the potential of offshore wind: A North Sea case study

Catalyst: Fast and Flexible Modeling of Reaction Networks

A Differentiable, Physics-Informed Ecosystem Modeling and Learning Framework for Large-Scale Inverse Problems: Demonstration with Photosynthesis Simulations

Forecasting Virus Outbreaks with Social Media Data Via Neural Ordinary Differential Equations

Mapping Out Phase Diagrams with Generative Classifiers

Extending JumpProcess.jl for Fast Point Process Simulation with Time-Varying Intensities

Differentiating Metropolis-Hastings to Optimize Intractable Densities

Modular Algorithms for Scientific Computing in Julia