Publications related to Inverse hyperbolic functions

VolRecon: Volume Rendering of Signed Ray Distance Functions for Generalizable Multi-View Reconstruction

The success of the Neural Radiance Fields (NeRF) in novel view synthesis has inspired researchers to propose neural implicit scene reconstruction. However, most existing neural implicit reconstruction methods optimize perscene parameters and therefore lack ...

2024

Noncollinear DFT plus U and Hubbard parameters with fully relativistic ultrasoft pseudopotentials

Nicola Marzari, Luca Binci

The magnetic, noncollinear parametrization of Dudarev's DFT + U method is generalized to fully relativistic ultrasoft pseudopotentials. We present the definition of the DFT + U total energy functional and the calculation of forces and stresses in the case ...

College Pk2023

Multiplicative chaos of the Brownian loop soup

Antoine Pierre François Jego, Titus Lupu

We construct a measure on the thick points of a Brownian loop soup in a bounded domain D

D

of the plane with given intensity theta>0

\theta >0

, which is formally obtained by exponentiating the square root of its occupation field. The measure is construct ...

WILEY2023

Addressing fairness in classification with a model-agnostic multi-objective algorithm

Boi Faltings, Claudiu-Cristian Musat, Diego Matteo Antognini

The goal of fairness in classification is to learn a classifier that does not discriminate against groups of individuals based on sensitive attributes, such as race and gender. One approach to designing fair algorithms is to use relaxations of fairness not ...

2021

Pulay forces in density-functional theory with extended Hubbard functionals: From nonorthogonalized to orthogonalized manifolds

Nicola Marzari, Iurii Timrov, Luca Binci, Matteo Cococcioni, Francesco Aquilante

We present a derivation of the exact expression for Pulay forces in density-functional theory calculations augmented with extended Hubbard functionals and arising from the use of orthogonalized atomic orbitals as projectors for the Hubbard manifold. The de ...

AMER PHYSICAL SOC2020

Inverse Modelling and Predictive Inference in Continuum Mechanics: a Data-Driven Approach

Claire Marianne Charlotte Capelo

The explosive growth of machine learning in the age of data has led to a new probabilistic and data-driven approach to solving very different types of problems. In this paper we study the feasibility of using such data-driven algorithms to solve classic ph ...

2020

On the Exact Gevrey Order of Formal Puiseux Series Solutions to the Third Painleve Equation

Andrey Vasilyev

In this paper, we study the third Painleve equation with parameters gamma = 0, alpha delta not equal 0. The Puiseux series formally satisfying this equation (after a certain change of variables) asymptotically approximate of Gevrey order one solutions to t ...

2019

Learning Positive Functions with Pseudo Mirror Descent

Negar Kiyavash

The nonparametric learning of positive-valued functions appears widely in machine learning, especially in the context of estimating intensity functions of point processes. Yet, existing approaches either require computing expensive projections or semidefin ...

Curran Associates, Inc.2019

Concentration compactness for critical radial wave maps

Joachim Krieger, Elisabetta Chiodaroli

We consider radially symmetric, energy critical wave maps from (1 + 2)-dimensional Minkowski space into the unit sphere

\mathbf{S}^m

, m≥1, and prove global regularity and scattering for classical smooth data of finite energy. In addition, we establish a ...

2018

Non-linear transfer function identification of pressure probes using Siren Disks

Jürg Alexander Schiffmann, Karim Magdi Zakaria Abdelrahman Shalash, Fatma Ceyhun Sahin

This article presents a Siren Disk proof of concept for the dynamic excitation of pressure probes, and a method to reconstruct distorted signals due to pneumatic channels. Constraints in sensor installation require placing a pressure transducer distant fro ...

2018

Inverse hyperbolic functions

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VolRecon: Volume Rendering of Signed Ray Distance Functions for Generalizable Multi-View Reconstruction

Noncollinear DFT plus U and Hubbard parameters with fully relativistic ultrasoft pseudopotentials

Multiplicative chaos of the Brownian loop soup

Addressing fairness in classification with a model-agnostic multi-objective algorithm

Pulay forces in density-functional theory with extended Hubbard functionals: From nonorthogonalized to orthogonalized manifolds

Inverse Modelling and Predictive Inference in Continuum Mechanics: a Data-Driven Approach

On the Exact Gevrey Order of Formal Puiseux Series Solutions to the Third Painleve Equation

Learning Positive Functions with Pseudo Mirror Descent

Concentration compactness for critical radial wave maps

Non-linear transfer function identification of pressure probes using Siren Disks

Addressing fairness in classification with a model-agnostic multi-objective algorithm

Inverse Modelling and Predictive Inference in Continuum Mechanics: a Data-Driven Approach

Pulay forces in density-functional theory with extended Hubbard functionals: From nonorthogonalized to orthogonalized manifolds

Learning Positive Functions with Pseudo Mirror Descent

On the Exact Gevrey Order of Formal Puiseux Series Solutions to the Third Painleve Equation

VolRecon: Volume Rendering of Signed Ray Distance Functions for Generalizable Multi-View Reconstruction

Non-linear transfer function identification of pressure probes using Siren Disks

Noncollinear DFT plus U and Hubbard parameters with fully relativistic ultrasoft pseudopotentials

Concentration compactness for critical radial wave maps

Multiplicative chaos of the Brownian loop soup