Trending Research
On the implementation of a robust and efficient finite element-based parallel solver for the compressible Navier-Stokes equations
The method is second-order accurate in time and space.
Numerical Analysis Numerical Analysis 35L65, 65M60, 65M12, 65N30
Dynamic Energy Management
We start with the simple setting of optimizing power flows in a static network, and then proceed to the case of optimizing dynamic power flows, i. e., power flows that change with time over a horizon.
Optimization and Control Portfolio Management
PySINDy: A Python package for the Sparse Identification of Nonlinear Dynamics from Data
PySINDy is a Python package for the discovery of governing dynamical systems models from data.
Dynamical Systems Computational Physics
Inertial Proximal Alternating Linearized Minimization (iPALM) for Nonconvex and Nonsmooth Problems
VLOGroup/mri-variationalnetwork
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In this paper we study nonconvex and nonsmooth optimization problems with semi-algebraic data, where the variables vector is split into several blocks of variables.
Optimization and Control
Gromov-Wasserstein Distances between Gaussian Distributions
MaximeVandegar/Papers-in-100-Lines-of-Code
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We also study the problem without restriction on the optimal plan, and provide lower and upper bounds for the value of the Gromov-Wasserstein distance between Gaussian distributions.
Probability
Convex optimization
First of all, the authors focused on the program of a two-semester course of lectures on convex optimization, which is given to students of MIPT.
Optimization and Control Numerical Analysis Numerical Analysis 65-01, 90-01, 65K05, 90C30, 90C90 G.1.6
Computing in Operations Research using Julia
The state of numerical computing is currently characterized by a divide between highly efficient yet typically cumbersome low-level languages such as C, C++, and Fortran and highly expressive yet typically slow high-level languages such as Python and MATLAB.
Optimization and Control Numerical Analysis Programming Languages
ADCME: Learning Spatially-varying Physical Fields using Deep Neural Networks
kailaix/ADCME.jl
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We express both the numerical simulations and DNNs using computational graphs and therefore, we can calculate the gradients using reverse-mode automatic differentiation.
Numerical Analysis Numerical Analysis
A spectral-Galerkin turbulent channel flow solver for large-scale simulations
A fully (pseudo-)spectral solver for direct numerical simulations of large-scale turbulent channel flows is described.
Numerical Analysis Numerical Analysis Fluid Dynamics
Last-mile Delivery: Optimal Locker Location Under Multinomial Logit Choice Model
Motivated by a real case in Singapore, we consider a POP-Locker Alliance who operates a set of POP-stations and wishes to improve the last-mile delivery by opening new locker facilities.
Optimization and Control
