Publications related to Newton's method in optimization

Phase diagram of the J-Jd Heisenberg model on the maple leaf lattice: Neural networks and density matrix renormalization group

Pratyay Ghosh, Ronny Thomale

We microscopically analyze the nearest-neighbor Heisenberg model on the maple leaf lattice through neural quantum state (NQS) and infinite density matrix renormalization group (iDMRG) methods. Embarking to parameter regimes beyond the exact dimer singlet g ...

Amer Physical Soc2024

Safe Zeroth-Order Convex Optimization Using Quadratic Local Approximations

Giancarlo Ferrari Trecate, Maryam Kamgarpour, Yuning Jiang, Baiwei Guo

We address black-box convex optimization problems, where the objective and constraint functions are not explicitly known but can be sampled within the feasible set. The challenge is thus to generate a sequence of feasible points converging towards an optim ...

2023

Tensor approximation of the self-diffusion matrix of tagged particle processes

Christoph Max Strössner

The objective of this paper is to investigate a new numerical method for the approximation of the self-diffusion matrix of a tagged particle process defined on a grid. While standard numerical methods make use of long-time averages of empirical means of de ...

ACADEMIC PRESS INC ELSEVIER SCIENCE2023

Geometrically-Conditioned Point Diffusion Models

Pascal Fua, Eduard Trulls Fortuny, Michal Jan Tyszkiewicz

Diffusion models generating images conditionally on text, such as Dall-E 2 [51] and Stable Diffusion[53], have recently made a splash far beyond the computer vision com- munity. Here, we tackle the related problem of generating point clouds, both unconditi ...

2023

GECCO: Geometrically-Conditioned Point Diffusion Models

Pascal Fua, Eduard Trulls Fortuny, Michal Jan Tyszkiewicz

Diffusion models generating images conditionally on text, such as Dall-E 2 [51] and Stable Diffusion[53], have recently made a splash far beyond the computer vision community. Here, we tackle the related problem of generating point clouds, both uncondition ...

Ieee Computer Soc2023

Variational methods for finding periodic orbits in the incompressible Navier Stokes equations

Tobias Schneider, Jeremy Peter Parker

Unstable periodic orbits are believed to underpin the dynamics of turbulence, but by their nature are hard to find computationally. We present a family of methods to converge such unstable periodic orbits for the incompressible Navier-Stokes equations, bas ...

CAMBRIDGE UNIV PRESS2022

Distributed Optimal Power Flow for VSC-MTDC Meshed AC/DC Grids Using ALADIN

Colin Neil Jones, Yuning Jiang, Xinliang Dai

The increasing application of voltage source converter (VSC) based high voltage direct current (VSC-HVDC) technology in power grids has raised the importance of incorporating DC grids and converters into the existing transmission network. This poses signif ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2022

Deficit Round-Robin: A Second Network Calculus Analysis

Jean-Yves Le Boudec, Seyed Mohammadhossein Tabatabaee

Deficit Round-Robin (DRR) is a widespread scheduling algorithm that provides fair queueing with variable-length packets. Bounds on worst-case delays for DRR were found by Boyer et al., who used a rigorous network calculus approach and characterized the ser ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2022

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Newton's method in optimization

Phase diagram of the J-Jd Heisenberg model on the maple leaf lattice: Neural networks and density matrix renormalization group

Safe Zeroth-Order Convex Optimization Using Quadratic Local Approximations

Tensor approximation of the self-diffusion matrix of tagged particle processes

Geometrically-Conditioned Point Diffusion Models

GECCO: Geometrically-Conditioned Point Diffusion Models

Variational methods for finding periodic orbits in the incompressible Navier Stokes equations

Characterization and prediction of peptide structures on inorganic surfaces

On the Double Descent of Random Features Models Trained with SGD

Distributed Optimal Power Flow for VSC-MTDC Meshed AC/DC Grids Using ALADIN

Deficit Round-Robin: A Second Network Calculus Analysis

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Chat with Graph Search

On the Double Descent of Random Features Models Trained with SGD

Deficit Round-Robin: A Second Network Calculus Analysis

Safe Zeroth-Order Convex Optimization Using Quadratic Local Approximations

Characterization and prediction of peptide structures on inorganic surfaces

Tensor approximation of the self-diffusion matrix of tagged particle processes

Phase diagram of the J-Jd Heisenberg model on the maple leaf lattice: Neural networks and density matrix renormalization group

Geometrically-Conditioned Point Diffusion Models

Variational methods for finding periodic orbits in the incompressible Navier Stokes equations

Distributed Optimal Power Flow for VSC-MTDC Meshed AC/DC Grids Using ALADIN

GECCO: Geometrically-Conditioned Point Diffusion Models