Publications related to Manifold

OSLO: On-the-Sphere Learning for Omnidirectional Images and Its Application to 360-Degree Image Compression

Pascal Frossard, Thomas Maugey, Roberto Gerson De Albuquerque Azevedo

State-of-the-art 2D image compression schemes rely on the power of convolutional neural networks (CNNs). Although CNNs offer promising perspectives for 2D image compression, extending such models to omnidirectional images is not straightforward. First, omn ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2022

Time Estimation of Polymer Translocation through Nano-Membrane

Maria-Alexandra Paun

In this paper, the charged polymer escapement phenomenon, via a little hole of nano-metric dimensions arranged in a constitutive biological membrane, is studied. We will present the case of the transport process of an ideal polymer in a 3-dimensional exten ...

MDPI2022

Algebra and geometry of link homology Lecture notes from the IHES 2021 Summer School

Oscar Salomon Kivinen

These notes cover the lectures of the first named author at 2021 IHES Summer School on "Enumerative Geometry, Physics and Representation Theory" with additional details and references. They cover the definition of Khovanov-Rozansky triply graded homology, ...

WILEY2022

The kinectome: A comprehensive kinematic map of human motion in health and disease

Enrico Amico, Antonella Romano, Emahnuel Troisi Lopez

Human voluntary movement stems from the coordinated activations in space and time of many musculoskeletal segments. However, the current methodological approaches to study human movement are still limited to the evaluation of the synergies among a few body ...

WILEY2022

Shrinking Scale Equidistribution for Monochromatic Random Waves on Compact Manifolds

Matthew De Courcy-Ireland

We prove equidistribution at shrinking scales for the monochromatic ensemble on a compact Riemannian manifold of any dimension. This ensemble on an arbitrary manifold takes a slowly growing spectral window in order to synthesize a random function. With hig ...

OXFORD UNIV PRESS2021

Realizing doubles: a conjugation zoo

Jérôme Scherer

Conjugation spaces are topological spaces equipped with an involution such that their fixed points have the same mod 2 cohomology (as a graded vector space, a ring and even an unstable algebra) but with all degrees divided by two, generalizing the classica ...

CAMBRIDGE UNIV PRESS2021

Slow-fast Dynamics of Strongly Coupled Adaptive Frequency Oscillators*

Auke Ijspeert, Jonas Buchli, Ludovic Righetti

Oscillators have two main limitations: their synchronization properties are limited (i.e., they have a finite synchronization region) and they have no memory of past interactions (i.e., they return to their intrinsic frequency whenever the entraining signa ...

SIAM PUBLICATIONS2021

Structure-Preserving Reduced Basis Methods For Poisson Systems

Jan Sickmann Hesthaven, Cecilia Pagliantini

We develop structure-preserving reduced basis methods for a large class of nondissipative problems by resorting to their formulation as Hamiltonian dynamical systems. With this perspective, the phase space is naturally endowed with a Poisson manifold struc ...

AMER MATHEMATICAL SOC2021

Efficient implementation of atom-density representations

Michele Ceriotti, Till Junge, Guillaume André Jean Fraux, 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

Geometry of the Loss Landscape in Overparameterized Neural Networks: Symmetries and Invariances

Wulfram Gerstner, Clément Hongler, Johanni Michael Brea, Francesco Spadaro, Berfin Simsek, Arthur Jacot

We study how permutation symmetries in overparameterized multi-layer neural networks generate `symmetry-induced' critical points. Assuming a network with

L

layers of minimal widths

r_1^*, \ldots, r_{L-1}^*

reaches a zero-loss minimum at $ r_1^*! \c ...

2021

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OSLO: On-the-Sphere Learning for Omnidirectional Images and Its Application to 360-Degree Image Compression

Time Estimation of Polymer Translocation through Nano-Membrane

Algebra and geometry of link homology Lecture notes from the IHES 2021 Summer School

The kinectome: A comprehensive kinematic map of human motion in health and disease

Shrinking Scale Equidistribution for Monochromatic Random Waves on Compact Manifolds

Realizing doubles: a conjugation zoo

Slow-fast Dynamics of Strongly Coupled Adaptive Frequency Oscillators*

Structure-Preserving Reduced Basis Methods For Poisson Systems

Efficient implementation of atom-density representations

Geometry of the Loss Landscape in Overparameterized Neural Networks: Symmetries and Invariances

OSLO: On-the-Sphere Learning for Omnidirectional Images and Its Application to 360-Degree Image Compression

Time Estimation of Polymer Translocation through Nano-Membrane

Realizing doubles: a conjugation zoo

Algebra and geometry of link homology Lecture notes from the IHES 2021 Summer School

The kinectome: A comprehensive kinematic map of human motion in health and disease

Shrinking Scale Equidistribution for Monochromatic Random Waves on Compact Manifolds

Structure-Preserving Reduced Basis Methods For Poisson Systems

Slow-fast Dynamics of Strongly Coupled Adaptive Frequency Oscillators*

Efficient implementation of atom-density representations

Geometry of the Loss Landscape in Overparameterized Neural Networks: Symmetries and Invariances