Cohomology of GKM fiber bundles

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Bundle-Specific Axon Diameter Index as a New Contrast to Differentiate White Matter Tracts

Jean-Philippe Thiran, Alessandro Daducci, Gabriel Girard, Cristina Granziera, David Paul Roger Romascano, Maxime Descoteaux, Muhamed Barakovic, Giorgio Innocenti

In the central nervous system of primates, several pathways are characterized by different spectra of axon diameters. In vivo methods, based on diffusion-weighted magnetic resonance imaging, can provide axon diameter index estimates non-invasively. However ...

2021

Representation Learning for Multi-relational Data

Eda Bayram

Recent years have witnessed a rise in real-world data captured with rich structural information that can be better depicted by multi-relational or heterogeneous graphs. However, research on relational representation learning has so far mostly focused on th ...

EPFL2021

Adaptive majority problems for restricted query graphs and for weighted sets

Doemoetoer Palvoelgyi, Abhishek Methuku, Balázs Keszegh

Suppose that the vertices of a graph G are colored with two colors in an unknown way. The color that occurs on more than half of the vertices is called the majority color (if it exists), and any vertex of this color is called a majority vertex. We study th ...

ELSEVIER2021

Three-dimensional fabrication of sub-micron optical waveguides in PDMS and other polymer materials

Giulia Panusa

Optical waveguides are one of the most important photonic components. They are indispensable tools in many of todayâ s technologies because of their capacity of guiding light. In particular, compact, low loss, flexible polymer optical waveguides are cruci ...

EPFL2021

node2coords: Graph Representation Learning with Wasserstein Barycenters

Pascal Frossard, Ntorina Thanou, Effrosyni Simou

In order to perform network analysis tasks, representations that capture the most relevant information in the graph structure are needed. However, existing methods learn representations that cannot be interpreted in a straightforward way and that are relat ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2021

Representing graphs through data with learning and optimal transport

Hermina Petric Maretic

Graphs offer a simple yet meaningful representation of relationships between data. This representation is often used in machine learning algorithms in order to incorporate structural or geometric information about data. However, it can also be used in an i ...

EPFL2021

Efficient Streaming Subgraph Isomorphism with Graph Neural Networks

Karl Aberer, Quoc Viet Hung Nguyen, Chi Thang Duong

Queries to detect isomorphic subgraphs are important in graph-based data management. While the problem of subgraph isomorphism search has received considerable attention for the static setting of a single query, or a batch thereof, existing approaches do n ...

ASSOC COMPUTING MACHINERY2021

An effective proof of the Cartan formula: The even prime

Anibal Maximiliano Medina Mardones

The Cartan formula encodes the relationship between the cup product and the action of the Steenrod algebra in F-p-cohomology. In this work, we present an effective proof of the Cartan formula at the cochain level when the field is F-2. More explicitly, for ...

2020

Orders That Are Etale-Locally Isomorphic

Eva Bayer Fluckiger, Mathieu Huruguen

Let R be a semilocal Dedekind domain with fraction field F. It is shown that two hereditary R-orders in central simple F-algebras that become isomorphic after tensoring with F and with some faithfully flat etale R-algebra are isomorphic. On the other hand, ...

AMER MATHEMATICAL SOC2020

Resolving bundle-specific intra-axonal T2 values within a voxel using diffusion-relaxation tract-based estimation

Jean-Philippe Thiran, Alessandro Daducci, Cristina Granziera, Erick Jorge Canales Rodriguez, Muhamed Barakovic

At the typical spatial resolution of MRI in the human brain, approximately 60–90% of voxels contain multiple fiber populations. Quantifying microstructural properties of distinct fiber populations within a voxel is therefore challenging but necessary. Whil ...

2020

Arithmetically rigid schemes via deformation theory of equivariant vector bundles

Maciej Emilian Zdanowicz

We analyze the deformation theory of equivariant vector bundles. In particular, we provide an effective criterion for verifying whether all infinitesimal deformations preserve the equivariant structure. As an application, using rigidity of the Frobenius ho ...

SPRINGER HEIDELBERG2021