News
1/6/2026
Avik Pal et al. present "Physics-Informed Neural Surrogates for Mesh-Invariant Modeling of High-Speed Flows" at AIAA SciTech 2026
1/1/2026
Avik Pal, Flemming Holtorf, Axel Larsson, Torkel Loman, Utkarsh, and Frank Schaefer publish NonlinearSolve.jl in ACM Transactions on Mathematical Software
10/14/2025
Evelyne Ringoot and Rabab Alomairy publish "A GPU-resident Memory-Aware Algorithm for Accelerating Bidiagonalization of Banded Matrices"
9/24/2025
Bowen Zhu and Songchen Tan release "Efficient Symbolic Computation via Hash Consing"
8/8/2025
Evelyne Ringoot, Rabab Alomairy, and Valentin Churavy publish "Performant Unified GPU Kernels for Portable Singular Value Computation Across Hardware and Precision"
7/4/2025
Vaibhav Dixit and David Hofmann co-author "Scientific machine learning of chaotic systems discovers governing equations for neural populations"
6/4/2025
Utkarsh et al. release "Physics-Constrained Flow Matching: Sampling Generative Models with Hard Constraints" (NeurIPS 2025)
5/26/2025
Avik Pal releases "Semi-Explicit Neural DAEs: Learning Long-Horizon Dynamical Systems with Algebraic Constraints"
1/28/2025
Songchen Tan releases "Scalable higher-order nonlinear solvers via higher-order automatic differentiation"
7/1/2024
Flemming Holtorf and Frank Schaefer publish "Performance Bounds for Quantum Feedback Control" in IEEE Transactions on Automatic Control
6/14/2024
Avik Pal and Frank Schaefer co-author "Differentiable Programming for Differential Equations: A Review"
3/12/2024
Avik Pal, Flemming Holtorf, Axel Larsson, Torkel Loman, Utkarsh, and Frank Schaefer release "NonlinearSolve.jl: High-Performance and Robust Solvers for Systems of Nonlinear Equations in Julia"
2/1/2024
Utkarsh and Valentin Churavy co-author "Automated translation and accelerated solving of differential equations on multiple GPU platforms" in Computer Methods in Applied Mechanics and Engineering
1/29/2024
Emily Nieves and Raj Dandekar publish "Uncertainty Quantified Discovery of Chemical Reaction Systems via Bayesian Scientific Machine Learning" in Frontiers in Systems Biology
12/1/2023
Chris Rackauckas presents "NonlinearSolve.jl: Efficient rootfinding and solving of algebraic equations in Julia" at JuliaCon Local Eindhoven
11/13/2023
Chris Rackauckas presents at the JuliaHEP 2023 Workshop in Erlangen on Automatic Differentiation, SciML, and maintaining large-scale Julia ecosystems
10/20/2023
Chris Rackauckas keynotes the LLNL Data-Driven Physical Simulations (DDPS) Seminar Series on "Generalizing Scientific Machine Learning and Differentiable Simulation Beyond Continuous Models"
8/29/2023
Chris Rackauckas presents "Improved Parallelism and Memory Performance Differentiating Stiff Differential Equations" at ICIAM 2023
7/27/2023
Chris Rackauckas keynotes ASE60 (Synergistic Interactions Between Theory and Computation) at MIT on translating theory to differential-equation software
7/24/2023
Chris Rackauckas keynotes JuliaCon 2023 with "Scientific Machine Learning through Symbolic Numerics"
5/5/2023
Chris Rackauckas presents "Extending Scientific Machine Learning to Agent-Based Models" at the ICLR 2023 AI4ABM Workshop
4/11/2021
MIT Julia Lab awarded a Climate Grand Challenge grant for briding computation with climate policymaking!
3/9/2021
MIT Julia Lab awarded Best Poster at the NeurIPS 2021 Differentiable Programming workshop for AbstractDifferentiation.jl!
11/17/2021
On 17th and 18th February 2022 there will be an introduction to Julia workshop at the Applied and Computational Mathematics (ACoM) laboratory, RWTH Aachen University.
11/11/2021
MIT + Pumas-AI + Roche team wins International Society of Pharmacology (ISoP) Mathematics and Computing Special Interest Group Award for "Automatic identification of non-obvious prognostic factors in big data with DeepNLME"
8/31/2021
SciML Receives Chan Zuckerberg Institute Funding: Spatial SSAs, Identifiability, and Compile Times
8/26/2021
SciML Common Interface Expansion
8/16/2021
SciML at JuliaCon 2021
5/24/2021
SciML Ecosystem Update: Improved QNDF Outperforms CVODE On SciMLBenchmarks
2/5/2021
SciML Ecosystem Update: GalacticOptim, GlobalSensitivity, Tutorials, and Documentation
1/19/2021
SciML Ecosystem Update: Bayesian Neural ODEs, Virtual Brownian Trees, Parallel Batching and More
9/5/2020
SciML Ecosystem Update: Koopman Optimization Under Uncertainty, Non-Commutative SDEs, GPUs in R, and More
8/17/2020
SciML Ecosystem Update: Neural PDEs, Lie Groups, and Stochastic Delay Differential Equations
8/10/2020
SciML Ecosystem Update: SDE Adjoints, FFORD Layers, and Jump Diffusion
6/1/2020
SciML Ecosystem Update: Auto-Parallelism and Component-Based Modeling
5/9/2020
SciML Ecosystem Update: Automated Model Discovery with DataDrivenDiffEq.jl and ReservoirComputing.jl
3/29/2020
SciML: An Open Source Software Organization for Scientific Machine Learning
3/23/2020
DifferentialEquations.jl v6.12.0: DAE Extravaganza
2/18/2020
DifferentialEquations.jl v6.11.0: Universal Differential Equation Overhaul
7/5/2019
DifferentialEquations.jl v6.7.0: GPU-based Ensembles and Automatic Sparsity
6/24/2019
DifferentialEquations.jl v6.6.0: Sparse Jacobian Coloring, Quantum Computer ODE Solvers, and Stiff SDEs
6/6/2019
DifferentialEquations.jl v6.5.0: Stiff SDEs, VectorContinuousCallback, Multithreaded Extrapolation
5/9/2019
DifferentialEquations.jl v6.4.0: Full GPU ODE, Performance, ModelingToolkit
2/2/2019
DifferentialEquations.jl 6.0: Radau5,Hyperbolic PDEs, Dependency Reductions
8/20/2018
DifferentialEquations.jl 5.0: v1.0,Jacobian Types, EPIRK
7/5/2018
DifferentialEquations.jl 4.6: Global Sensitivity Analysis, Variable Order Adams
5/26/2018
DifferentialEquations.jl 4.5: ABC, Adaptive Multistep, Maximum A Posteriori
4/30/2018
A ''Jupyter'' of DiffEq: Introducing Python and R Bindings for DifferentialEquations.jl
4/13/2018
DifferentialEquations.jl 4.4: Enhanced Stability and IMEX SDE Integrators
4/9/2018
DifferentialEquations.jl 4.3: Automatic Stiffness Detection and Switching
3/31/2018
DifferentialEquations.jl 4.2: Krylov Exponential Integrators, Non-Diagonal Adaptive SDEs, Tau-Leaping
2/17/2018
DifferentialEquations.jl 4.1: New ReactionDSL and KLU Sundials
1/24/2018
DifferentialEquations.jl 4.0: Breaking Syntax Changes, Adjoint Sensitivity, Bayesian Estimation, and ETDRK4
1/15/2018
DifferentialEquations.jl 3.4: Sundials 3.1, ARKODE, Static Arrays
12/11/2017
DifferentialEquations.jl 3.2: Expansion of Event Compatibility
11/24/2017
DifferentialEquations.jl 3.1: Jacobian Passing
8/25/2017
Stiff SDE and DDE Solvers
8/13/2017
SDIRK Methods
7/6/2017
SDIRK Methods
5/17/2017
Filling In The Interop Packages and Rosenbrock
4/30/2017
DifferentialEquations.jl 2.0
4/7/2017
DifferentialEquations.jl v1.9.1
4/4/2017
DifferentialEquations.jl Workshop at JuliaCon 2017
2/2/2017
DifferentialEquations.jl v1.8.0
1/14/2017
DifferentialEquations.jl v1.6.0
1/8/2017
base
1/5/2017
PDEs Update
1/1/2017
DifferentialEquations.jl 3.3: IMEX Solvers
11/26/2016
Hello World!!
1/21/2016
OrdinaryDiffEq v0.5