Concept

Riemannian geometry

Related publications (188)

Escaping from saddle points on Riemannian manifolds

Nicolas Henri Bernard Flammarion, Yue Sun

We consider minimizing a nonconvex, smooth function f on a Riemannian manifold M. We show that a perturbed version of Riemannian gradient descent algorithm converges to a second-order stationary point (and hence is able to escape saddle points on the manif ...

2019

A Gauss-Bonnet Theorem for Asymptotically Conical Manifolds and Manifolds with Conical Singularities

Adrien Giuliano Marcone

The purpose of this thesis is to provide an intrinsic proof of a Gauss-Bonnet-Chern formula for complete Riemannian manifolds with finitely many conical singularities and asymptotically conical ends. A geometric invariant is associated to the link of both ...

EPFL2019

Design optimization of a CFRP-aluminum joint for a bioengineering application

John Botsis, Georgios Pappas

Lightweight design demands and complexity requirements of modern high-end structures in aerospace, automotive, sports and bioengineering can be successfully covered by a combination of fiber reinforced polymers (FRPs) with metallic components. Conventional ...

Cambridge University Press (CUP)2019

Bayesian Optimization Meets Riemannian Manifolds in Robot Learning

Sylvain Calinon, Noémie Laure Gwendoline Jaquier

Bayesian optimization (BO) recently became popular in robotics to optimize control parameters and parametric policies in direct reinforcement learning due to its data efficiency and gradient-free approach. However, its performance may be seriously compromi ...

2019

Improved Bounds for Discretization of Langevin Diffusions: Near-Optimal Rates without Convexity

Nicolas Henri Bernard Flammarion

We consider minimizing a nonconvex, smooth function

f

on a Riemannian manifold

\mathcal{M}

. We show that a perturbed version of Riemannian gradient descent algorithm converges to a second-order stationary point (and hence is able to escape saddle point ...

2019

A central limit theorem for integrals of random waves

Marius Christopher Lemm, Matthew De Courcy-Ireland

We derive a central limit theorem for the mean-square of random waves in the high-frequency limit over shrinking sets. Our proof applies to any compact Riemannian manifold of arbitrary dimension, thanks to the universality of the local Weyl law. The key te ...

2019

Renormalization of quantum field theory on Riemannian manifolds

In this paper, we provide a simple pedagogical proof of the existence of covariant renormalizations in Euclidean perturbative quantum field theory on closed Riemannian manifolds, following the Epstein–Glaser philosophy. We rely on a local method that allow ...

2019

A Learned Shape-Adaptive Subsurface Scattering Model

Wenzel Alban Jakob, Delio Aleardo Vicini

Subsurface scattering, in which light refracts into a translucent material to interact with its interior, is the dominant mode of light transport in many types of organic materials. Accounting for this phenomenon is thus crucial for visual realism, but exp ...

ASSOC COMPUTING MACHINERY2019

Parametric Workshop

Yves Weinand, Petras Vestartas, Nicolas Henry Pierre Louis Rogeau

This bi-annual workshop is an introduction to parametric design for Master 1 students following Studio Weinand. The following topics are being discussed: impact of digital technologies on the design process, fabrication and assembly constraints, collaborat ...

2019

Adhesive wear mechanisms in the presence of weak interfaces: Insights from an amorphous model system

Jean-François Molinari, Tobias Brink

Engineering wear models are generally empirical and lack connections to the physical processes of debris generation at the nanoscale to microscale. Here, we thus analyze wear particle formation for sliding interfaces in dry contact with full and reduced ad ...

2019

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Improved Bounds for Discretization of Langevin Diffusions: Near-Optimal Rates without Convexity

Nicolas Henri Bernard Flammarion

We consider minimizing a nonconvex, smooth function

f

on a Riemannian manifold

\mathcal{M}

. We show that a perturbed version of Riemannian gradient descent algorithm converges to a second-order stationary point (and hence is able to escape saddle point ...

2019