Publications related to Distribution (mathematics)

Moment approach of the multi-species non-linear Coulomb collision operator adapted to particle-in-cell codes

Laurent Villard, Stephan Brunner, Emmanuel Lanti, Moahan Murugappan, Noé Thomas Elie Ohana, Claudio Gheller

In this article an approximated version of the multi-species, non-linear Coulomb collision operator is derived via the use of a truncated moment expansion of the distribution function to compute the Rosenbluth potentials. The evolution of the distribution ...

IOP PUBLISHING LTD2021

Effect of collisions on non-adiabatic electron dynamics in ITG-driven microturbulence

Stephan Brunner, Justin Richard Ball

Non-adiabatic electron response leads to significant changes in ion temperature gradient (ITG) eigenmodes, leading, in particular, to fine-structures that are significantly extended along the magnetic field lines at corresponding mode rational surfaces (MR ...

AIP Publishing2021

Generating Smooth Pose Sequences for Diverse Human Motion Prediction

Mathieu Salzmann, Wei Mao

Recent progress in stochastic motion prediction, i.e., predicting multiple possible future human motions given a single past pose sequence, has led to producing truly diverse future motions and even providing control over the motion of some body parts. How ...

IEEE2021

A first-order primal-dual method with adaptivity to local smoothness

Volkan Cevher, Maria-Luiza Vladarean

We consider the problem of finding a saddle point for the convex-concave objective

\min_x \max_y f(x) + \langle Ax, y\rangle - g^*(y)

, where

f

is a convex function with locally Lipschitz gradient and

g

is convex and possibly non-smooth. We propose an ...

2021

Atomic subgraphs and the statistical mechanics of networks

Sofia Charlotta Olhede

We develop random graph models where graphs are generated by connecting not only pairs of vertices by edges, but also larger subsets of vertices by copies of small atomic subgraphs of arbitrary topology. This allows for the generation of graphs with extens ...

2021

Efficient implementation of atom-density representations

Michele Ceriotti, Guillaume André Jean Fraux, Till Junge, Félix Benedito Clément Musil, Michael John Willatt, Max David Veit, Alexander Jan Goscinski

Physically motivated and mathematically robust atom-centered representations of molecular structures are key to the success of modern atomistic machine learning. They lie at the foundation of a wide range of methods to predict the properties of both materi ...

2021

CryoGAN: A New Reconstruction Paradigm for Single-Particle Cryo-EM Via Deep Adversarial Learning

Michaël Unser, Laurène Donati, Harshit Gupta, Michael Thompson McCann

We present CryoGAN, a new paradigm for single-particle cryo-electron microscopy (cryo-EM) reconstruction based on unsupervised deep adversarial learning. In single-particle cryo-EM, the structure of a biomolecule needs to be reconstructed from a large set ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2021

Fourier uniqueness in even dimensions

Maryna Viazovska

In recent work, methods from the theory of modular forms were used to obtain Fourier uniqueness results in several key dimensions (d = 1, 8, 24), in which a function could be uniquely reconstructed from the values of it and its Fourier transform on a discr ...

2021

Distribution (mathematics)

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Moment approach of the multi-species non-linear Coulomb collision operator adapted to particle-in-cell codes

Effect of collisions on non-adiabatic electron dynamics in ITG-driven microturbulence

Generating Smooth Pose Sequences for Diverse Human Motion Prediction

A first-order primal-dual method with adaptivity to local smoothness

Atomic subgraphs and the statistical mechanics of networks

Efficient implementation of atom-density representations

CryoGAN: A New Reconstruction Paradigm for Single-Particle Cryo-EM Via Deep Adversarial Learning

Fourier uniqueness in even dimensions

Moment approach of the multi-species non-linear Coulomb collision operator adapted to particle-in-cell codes

A first-order primal-dual method with adaptivity to local smoothness

CryoGAN: A New Reconstruction Paradigm for Single-Particle Cryo-EM Via Deep Adversarial Learning

Atomic subgraphs and the statistical mechanics of networks

Fourier uniqueness in even dimensions

Efficient implementation of atom-density representations

Generating Smooth Pose Sequences for Diverse Human Motion Prediction

Effect of collisions on non-adiabatic electron dynamics in ITG-driven microturbulence