Publications related to A General Theory of Equivariant CNNs on Homogeneous Spaces

Related publications (33)

Geometric Learning: Leveraging differential geometry for learning and control

In this thesis, we concentrate on advancing high-level behavioral control policies for robotic systems within the framework of Dynamical Systems (DS). Throughout the course of this research, a unifying thread weaving through diverse fields emerges, and tha ...

EPFL2024

Anomalous and Chern topological waves in hyperbolic networks

Romain Christophe Rémy Fleury, Haoye Qin, Zhe Zhang, Aleksi Antoine Bossart, Zhechen Zhang

Hyperbolic lattices are a new type of synthetic materials based on regular tessellations in non-Euclidean spaces with constant negative curvature. While so far, there has been several theoretical investigations of hyperbolic topological media, experimental ...

Nature Research2024

Band Gap Renormalization at Different Symmetry Points in Perovskites

Majed Chergui, Lijie Wang

Using ultrafast broad-band transient absorption (TA) spectroscopy of photoexcited MAPbBr3 thin films with probe continua in the visible and the mid- to deep-ultraviolet (UV) ranges, we capture the ultrafast renormalization at the fundamental gap at the R s ...

Amer Chemical Soc2024

'Fraternal-twin' ferroelectricity: competing polar states in hydrogen-doped samarium nickelate from first principles

Michele Kotiuga

In ferroelectric switching, an applied electric field switches the system between two polar symmetry-equivalent states. In this work, we use first-principles calculations to explore the polar states of hydrogen-doped samarium nickelate (SNO) at a concentra ...

Iop Publishing Ltd2024

Cochains are all you need

Kelly Spry Maggs

In this thesis, we apply cochain complexes as an algebraic model of space in a diverse range of mathematical and scientific settings. We begin with an algebraic-discrete Morse theory model of auto-encoding cochain data, connecting the homotopy theory of d ...

EPFL2024

Mean value theorems for collections of lattices with a prescribed group of symmetries

Nihar Prakash Gargava

Euclidean lattices are mathematical objects of increasing interest in the fields of cryptography and error-correcting codes. This doctoral thesis is a study on high-dimensional lattices with the motivation to understand how efficient they are in terms of b ...

EPFL2024

Complex Representation Learning with Graph Convolutional Networks for Knowledge Graph Alignment

Quoc Viet Hung Nguyen, Thành Tâm Nguyên, Thanh Trung Huynh

The task of discovering equivalent entities in knowledge graphs (KGs), so-called KG entity alignment, has drawn much attention to overcome the incompleteness problem of KGs. The majority of existing techniques learns the pointwise representations of entiti ...

Wiley-Hindawi2023

Towards Stable and Efficient Adversarial Training against $l_1$ Bounded Adversarial Attacks

Sabine Süsstrunk, Mathieu Salzmann, Chen Liu, Yulun Jiang

We address the problem of stably and efficiently training a deep neural network robust to adversarial perturbations bounded by an

l_1

norm. We demonstrate that achieving robustness against

l_1

-bounded perturbations is more challenging than in the

l_2

...

2023

A structured prediction approach for robot imitation learning

Aude Billard, Iason Batzianoulis

We propose a structured prediction approach for robot imitation learning from demonstrations. Among various tools for robot imitation learning, supervised learning has been observed to have a prominent role. Structured prediction is a form of supervised le ...

Sage Publications Ltd2023

Critical line of the triangular Ising antiferromagnet in a field from a C3-symmetric corner transfer matrix algorithm

Afonso Dos Santos Rufino, Frédéric Mila, Jeanne Colbois, Samuel Louis Nyckees

The corner transfer matrix renormalization group (CTMRG) algorithm has been extensively used to investigate both classical and quantum two-dimensional (2D) lattice models. The convergence of the algorithm can strongly vary from model to model depending on ...

Amer Physical Soc2023

On A Special Symmetry In The Dynamics Of Complex Systems In A Holographic-Type Perspective

Maria-Alexandra Paun

By operating with the Scale Relativity Theory in the dynamics of complex systems, we can achieve a description of these complex systems through a holographic-type perspective. Then, gauge invariances of a Riccati-type become functional in complex system dy ...

UNIV POLITEHNICA BUCHAREST, SCI BULL2023

Berry curvature dipole generation and helicity-to-spin conversion at symmetry-mismatched heterointerfaces

Peng Chen, Xupeng Yang

The Berry curvature dipole (BCD) is a key parameter that describes the geometric nature of energy bands in solids. It defines the dipole-like distribution of Berry curvature in the band structure and plays a key role in emergent nonlinear phenomena. The th ...

Nature Portfolio2023

Dynamic nuclear polarisation of 1H in Gd-doped In(OH)3

David Lyndon Emsley, Michael Allan Hope, Amrit Venkatesh, Yuxuan Zhang

Dynamic nuclear polarisation (DNP) of solids doped with high-spin metal ions, such as Gd3+, is a useful strategy to enhance the nuclear magnetic resonance (NMR) sensitivity for these samples. Spin diffusion can relay polarisation throughout a sample, which ...

Academic Press Inc - Elsevier Science2023

Retraction-based numerical methods for continuation, interpolation and time integration on manifolds

Axel Elie Joseph Séguin

The goal of this thesis is the development and the analysis of numerical methods for problems where the unknown is a curve on a smooth manifold. In particular, the thesis is structured around the three following problems: homotopy continuation, curve inter ...

EPFL2023

Deep Learning Generalization with Limited and Noisy Labels

Mahsa Forouzesh

Deep neural networks have become ubiquitous in today's technological landscape, finding their way in a vast array of applications. Deep supervised learning, which relies on large labeled datasets, has been particularly successful in areas such as image cla ...

EPFL2023

Hybrid Quadratic Programming - Pullback Bundle Dynamical Systems Control

Aude Billard, Bernardo Fichera

Dynamical System (DS)-based closed-loop control is a simple and effective way to generate reactive motion policies that well generalize to the robotic workspace, while retaining stability guarantees. Lately the formalism has been expanded in order to handl ...

SPRINGER INTERNATIONAL PUBLISHING AG2023

Fundamental Limits in Statistical Learning Problems: Block Models and Neural Networks

Elisabetta Cornacchia

This thesis focuses on two selected learning problems: 1) statistical inference on graphs models, and, 2) gradient descent on neural networks, with the common objective of defining and analysing the measures that characterize the fundamental limits. In th ...

EPFL2023

Non-Gaussian superradiant transition via three-body ultrastrong coupling

Fabrizio Minganti

We introduce a class of quantum optical Hamiltonians characterized by three-body couplings and propose a circuit-QED scheme based on state-of-the-art technology that implements the considered model. Unlike two-body light-matter interactions, this three-bod ...

AMER PHYSICAL SOC2023

Polarization-Controlled Chromo-Encryption

Olivier Martin, Hsiang-Chu Wang

The response of simple plasmonic nanorods to polarized illumination is studied in detail. Depending on the orientation of that polarization with respect to the symmetry axes of the nanostructure, a chiral response can occur, which can be analyzed through a ...

WILEY-V C H VERLAG GMBH2023

Predicting nonlinear optical scattering with physics-driven neural networks

Demetri Psaltis, Carlo Gigli

Deep neural networks trained on physical losses are emerging as promising surrogates for nonlinear numerical solvers. These tools can predict solutions to Maxwell's equations and compute gradients of output fields with respect to the material and geometric ...

AIP Publishing2023