Trending Research
Angular Synchronization by Eigenvectors and Semidefinite Programming
The angular synchronization problem is to obtain an accurate estimation (up to a constant additive phase) for a set of unknown angles $\theta_1,...,\theta_n$ from $m$ noisy measurements of their offsets $\theta_i-\theta_j \mod 2\pi$.
Spectral Theory 15A52; 65F15; 05C80
Asynchronous and Parallel Distributed Pose Graph Optimization
We present Asynchronous Stochastic Parallel Pose Graph Optimization (ASAPP), the first asynchronous algorithm for distributed pose graph optimization (PGO) in multi-robot simultaneous localization and mapping.
Optimization and Control Multiagent Systems Robotics
Differentiating through Log-Log Convex Programs
We use the adjoint of the derivative to implement differentiable log-log convex optimization layers in PyTorch and TensorFlow.
Optimization and Control
PowerModels.jl: An Open-Source Framework for Exploring Power Flow Formulations
This work provides a brief introduction to the design of PowerModels, validates its implementation, and demonstrates its effectiveness with a proof-of-concept study analyzing five different formulations of the Optimal Power Flow problem.
Optimization and Control Computational Engineering, Finance, and Science
Universal Average-Case Optimality of Polyak Momentum
d2l-ai/d2l-en
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Polyak momentum (PM), also known as the heavy-ball method, is a widely used optimization method that enjoys an asymptotic optimal worst-case complexity on quadratic objectives.
Optimization and Control
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
Computing Dynamic User Equilibria on Large-Scale Networks: From Theory to Software Implementation
Dynamic user equilibrium (DUE) is the most widely studied form of dynamic traffic assignment, in which road travelers engage in a non-cooperative Nash-like game with departure time and route choices.
Optimization and Control Analysis of PDEs
QPALM: A Proximal Augmented Lagrangian Method for Nonconvex Quadratic Programs
The resulting implementation is shown to be extremely robust in numerical simulations, solving all of the Maros-Meszaros problems and finding a stationary point for most of the nonconvex QPs in the Cutest test set.
Optimization and Control 90C05, 90C20, 90C26, 49J53, 49M15
Stiff-PINN: Physics-Informed Neural Network for Stiff Chemical Kinetics
Consequently, we employ Quasi-Steady-State-Assumptions (QSSA) to reduce the stiffness of the ODE systems, and the PINN then can be successfully applied to the converted non/mild-stiff systems.
Numerical Analysis Numerical Analysis Chemical Physics Computational Physics
Solving Inverse Problems in Steady-State Navier-Stokes Equations using Deep Neural Networks
We propose a general and robust approach for solving inverse problems in the steady-state Navier-Stokes equations by combining deep neural networks and numerical partial differential equation (PDE) schemes.
Numerical Analysis Numerical Analysis