Publications associées à Quantifications canoniques

Convex Quantization Preserves Logconcavity

A logconcave likelihood is as important to proper statistical inference as a convex cost function is important to variational optimization. Quantization is often disregarded when writing likelihood models, ignoring the limitations of the physical detectors ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2022

Rank-adaptive structure-preserving model order reduction of Hamiltonian systems

Jan Sickmann Hesthaven, Nicolò Ripamonti, Cecilia Pagliantini

This work proposes an adaptive structure-preserving model order reduction method for finite-dimensional parametrized Hamiltonian systems modeling non-dissipative phenomena. To overcome the slowly decaying Kolmogorov width typical of transport problems, the ...

EDP SCIENCES S A2022

From SU(2)5 to SU(2)3 Wess-Zumino-Witten transitions in a frustrated spin-52 chain

Frédéric Mila, Natalia Chepiga

We investigate the properties of a frustrated spin-5/2 chain with next-nearest-neighbor two- and three-site interactions, with two questions in mind: the nature of the transition into the dimerized phase induced by the three-site interaction, and the possi ...

AMER PHYSICAL SOC2022

Elimination of ringing artifacts by finite-element projection in FFT-based homogenization

Till Junge, Ali Falsafi, Martin Ladecký

Micromechanical homogenization is often carried out with Fourier-accelerated methods that are prone to ringing artifacts. We here generalize the compatibility projection introduced by Vond.rejc et al. (2014) [24] beyond the Fourier basis. In particular, we ...

ACADEMIC PRESS INC ELSEVIER SCIENCE2022

Temporally-Coherent Surface Reconstruction via Metric-Consistent Atlases

Pascal Fua, Mathieu Salzmann, Shaifali Parashar, Jan Bednarík, Siddhartha Chaudhuri

We propose a method for the unsupervised reconstruction of a temporally-coherent sequence of surfaces from a sequence of time-evolving point clouds, yielding dense, semantically meaningful correspondences between all keyframes. We represent the reconstruct ...

2021

Optimized Quantization in Distributed Graph Signal Filtering

Pascal Frossard, Isabela Cunha Maia Nobre

Distributed graph signal processing algorithms require the network nodes to communicate by exchanging messages in order to achieve a common objective. These messages have a finite precision in realistic networks, which may necessitate to implement message ...

2019

Symplectic Model-Reduction with a Weighted Inner Product

Jan Sickmann Hesthaven, Babak Maboudi Afkham

In the recent years, considerable attention has been paid to preserving structures and invariants in reduced basis methods, in order to enhance the stability and robustness of the reduced system. In the context of Hamiltonian systems, symplectic model redu ...

2018

Heat kernel methods for Lifshitz theories

Diego Blas Temino, Mario Herrero Valea

We study the one-loop covariant effective action of Lifshitz theories using the heat kernel technique. The characteristic feature of Lifshitz theories is an anisotropic scaling between space and time. This is enforced by the existence of a preferred foliat ...

Springer2017

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Quantifications canoniques

Convex Quantization Preserves Logconcavity

Rank-adaptive structure-preserving model order reduction of Hamiltonian systems

From SU(2)5 to SU(2)3 Wess-Zumino-Witten transitions in a frustrated spin-52 chain

Elimination of ringing artifacts by finite-element projection in FFT-based homogenization

Temporally-Coherent Surface Reconstruction via Metric-Consistent Atlases

Finite-Level Quantization Procedures for Construction and Decoding of Polar Codes

Optimized Quantization in Distributed Graph Signal Filtering

The S-matrix bootstrap. Part III: higher dimensional amplitudes

Symplectic Model-Reduction with a Weighted Inner Product

Heat kernel methods for Lifshitz theories

Graph Chatbot

Chattez avec Graph Search

From SU(2)5 to SU(2)3 Wess-Zumino-Witten transitions in a frustrated spin-52 chain

Finite-Level Quantization Procedures for Construction and Decoding of Polar Codes

Optimized Quantization in Distributed Graph Signal Filtering

The S-matrix bootstrap. Part III: higher dimensional amplitudes

Symplectic Model-Reduction with a Weighted Inner Product

Convex Quantization Preserves Logconcavity

Rank-adaptive structure-preserving model order reduction of Hamiltonian systems

Elimination of ringing artifacts by finite-element projection in FFT-based homogenization

Heat kernel methods for Lifshitz theories

Temporally-Coherent Surface Reconstruction via Metric-Consistent Atlases