Showing 1–20 of 24 results
/ Date/ Name
Nov 10, 2021Physics-enhanced deep surrogates for partial differential equationsJul 17, 2019A Differentiable Programming System to Bridge Machine Learning and Scientific ComputingOct 16, 2022Automatic Differentiation of Programs with Discrete RandomnessMar 31, 2023A Practitioner's Guide to Bayesian Inference in Pharmacometrics using PumasMar 16, 2026Scientific Machine Learning-assisted Model Discovery from Telemetry DataDec 14, 2020Bayesian Neural Ordinary Differential EquationsMar 3, 2023Locally Regularized Neural Differential Equations: Some Black Boxes Were Meant to Remain Closed!Jul 23, 2020A machine learning aided global diagnostic and comparative tool to assess effect of quarantine control in Covid-19 spreadMay 12, 2021Composing Modeling and Simulation with Machine Learning in JuliaMar 9, 2021ModelingToolkit: A Composable Graph Transformation System For Equation-Based ModelingJan 29, 2022Symbolic-Numeric Integration of Univariate Expressions based on Sparse RegressionSep 25, 2021AbstractDifferentiation.jl: Backend-Agnostic Differentiable Programming in JuliaApr 8, 2022ReservoirComputing.jl: An Efficient and Modular Library for Reservoir Computing ModelsMar 2, 2023Robust Parameter Estimation for Rational Ordinary Differential EquationsAug 26, 2022DelayDiffEq: Generating Delay Differential Equation Solvers via Recursive Embedding of Ordinary Differential Equation SolversJan 10, 2023Differentiable modeling to unify machine learning and physical models and advance GeosciencesFeb 6, 2019DiffEqFlux.jl - A Julia Library for Neural Differential EquationsMar 22, 2023Efficient hybrid modeling and sorption model discovery for non-linear advection-diffusion-sorption systems: A systematic scientific machine learning approachJul 19, 2021NeuralPDE: Automating Physics-Informed Neural Networks (PINNs) with Error ApproximationsOct 7, 2020Accelerating Simulation of Stiff Nonlinear Systems using Continuous-Time Echo State Networks