Publications related to GRAPH-STRUCTURED TENSOR OPTIMIZATION FOR NONLINEAR DENSITY CONTROL AND MEAN FIELD GAMES

Related publications (12)

Advances in Algorithms for Sampling, Optimization and Inference in Disordered Systems

This thesis focuses on the development of advanced algorithmic techniques, primarily Markov Chain Monte Carlo (MCMC) methods, and message passing algorithms, to tackle high-dimensional optimization and inference problems. The algorithms used have a probabi ...

EPFL2024

Solving Inverse PDE Problems using Grid-Free Monte Carlo Estimators

Ekrem Fatih Yilmazer, Wenzel Alban Jakob

Partial differential equations can model diverse physical phenomena including heat diffusion, incompressible flows, and electrostatic potentials. Given a description of an object's boundary and interior, traditional methods solve such PDEs by densely meshi ...

Association for Computing Machinery (ACM)2024

Optimizing Two-Truck Platooning With Deadlines

Wenjie Xu

We study a transportation problem where two heavy-duty trucks travel across the national highway from separate origins to destinations, subject to individual deadline constraints. Our objective is to minimize their total fuel consumption by jointly optimiz ...

IEEE Institute of Electrical and Electronics Engineers2023

Tensor train for global optimization problems in robotics

Sylvain Calinon, Tobias Löw, Suhan Narayana Shetty

The convergence of many numerical optimization techniques is highly dependent on the initial guess given to the solver. To address this issue, we propose a novel approach that utilizes tensor methods to initialize existing optimization solvers near global ...

Sage Publications Ltd2023

Approximation of Lipschitz Functions Using Deep Spline Neural Networks

Michaël Unser, Alexis Marie Frederic Goujon, Pakshal Narendra Bohra, Sebastian Jonas Neumayer

Although Lipschitz-constrained neural networks have many applications in machine learning, the design and training of expressive Lipschitz-constrained networks is very challenging. Since the popular rectified linear-unit networks have provable disadvantage ...

2023

Family of Gaussian wavepacket dynamics methods from the perspective of a nonlinear Schrodinger equation

Jiri Vanicek

Many approximate solutions of the time-dependent Schrodinger equation can be formulated as exact solutions of a nonlinear Schrodinger equation with an effective Hamiltonian operator depending on the state of the system. We show that Heller's thawed Gaussia ...

2023

Data-driven distributionally robust joint chance-constrained energy management for multi-energy microgrid

Colin Neil Jones, Yuning Jiang

Multi-energy microgrid (MEMG) has the potential to improve the energy utilization efficiency. However, the uncertainty caused by distributed renewable energy resources brings an urgent need for multi-energy co -optimization to ensure secure operation. This ...

2022

A computational model applied to myocardial perfusion in the human heart: From large coronaries to microvasculature

Alfio Quarteroni

In this paper we present a mathematical and numerical model for human cardiac perfusion which accounts for the different length scales of the vessels in the coronary tree. Epicardial vessels are represented with fully three-dimensional (3D) fluid-dynamics, ...

2021

Learning Over Multitask Graphs-Part II: Performance Analysis

Ali H. Sayed, Stefan Vlaski, Roula Nassif

Part I of this paper formulated a multitask optimization problem where agents in the network have individual objectives to meet, or individual parameter vectors to estimate, subject to a smoothness condition over the graph. A diffusion strategy was devised ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2020

Complexity-efficient Fano Decoding of Polarization-adjusted Convolutional (PAC) Codes

Andreas Peter Burg

Polarization-adjusted convolutional (PAC) codes are modified polar codes in which a one-to-one convolutional transformation is employed before the classical polar transform. Fano decoding of PAC codes in the Shannon lecture at ISIT2019 showed an outstandin ...

IEEE2020

Nonlinear numerical analysis of R-UHPFRC railway Π-beams

Eugen Brühwiler, Xiujiang Shen

2016

Can tournament selection improve performances of the classical particle swarm optimization algorithm?

Juan Ramon Mosig, Ivica Stevanovic, Ruzica Golubovic

2009