Polar Codes: Characterization of Exponent, Bounds, and Constructions

Chat with Graph Search

Ask any question about EPFL courses, lectures, exercises, research, news, etc. or try the example questions below.

DISCLAIMER: The Graph Chatbot is not programmed to provide explicit or categorical answers to your questions. Rather, it transforms your questions into API requests that are distributed across the various IT services officially administered by EPFL. Its purpose is solely to collect and recommend relevant references to content that you can explore to help you answer your questions.

Deep learning has shown remarkable potential for industrial applications, particularly in predictive maintenance and condition monitoring. A key challenge in this domain is prognostics, specifically predicting the Remaining Useful Life (RUL) of assets - a ...

This work is concerned with the computation of the action of a matrix function f(A), such as the matrix exponential or the matrix square root, on a vector b. For a general matrix A, this can be done by computing the compression of A onto a suitable Krylov ...

It is well known that a family of n×n commuting matrices can be simultaneously triangularized by a unitary similarity transformation. The diagonal entries of the triangular matrices define the n joint eigenvalues of the family. In this work, we consider th ...

We present a fundamental improvement of a high polynomial degree time domain cell method recently introduced by the last three authors. The published work introduced a method featuring block-diagonal system matrices where the block size and conditioning sc ...

The increasing complexity of transformer models in artificial intelligence expands their computational costs, memory usage, and energy consumption. Hardware acceleration tackles the ensuing challenges by designing processors and accelerators tailored for t ...

In this thesis we will present and analyze randomized algorithms for numerical linear algebra problems. An important theme in this thesis is randomized low-rank approximation. In particular, we will study randomized low-rank approximation of matrix functio ...

Spectral algorithms are some of the main tools in optimization and inference problems on graphs. Typically, the graph is encoded as a matrix and eigenvectors and eigenvalues of the matrix are then used to solve the given graph problem. Spectral algorithms ...

Materials for high -temperature environments are actively being investigated for deployment in aerospace and nuclear applications. This study uses computational approaches to unravel the crystallography and thermodynamics of a promising class of refractory ...

A key challenge across many disciplines is to extract meaningful information from data which is often obscured by noise. These datasets are typically represented as large matrices. Given the current trend of ever-increasing data volumes, with datasets grow ...

Given a family of nearly commuting symmetric matrices, we consider the task of computing an orthogonal matrix that nearly diagonalizes every matrix in the family. In this paper, we propose and analyze randomized joint diagonalization (RJD) for performing t ...

Negative triangularity (NT) scenarios in TCV have been compared to positive triangularity (PT) scenarios using the same plasma shapes foreseen for divertor tokamak test tokamak operations. The experiments provided a NT/PT L-mode pair and a PT H-mode with d ...

In this work, we study the impact of aspect ratio A = R 0 / r (the ratio of major radius R 0 to minor radius r) on the confinement benefits of negative triangularity (NT) plasma shaping. We use high-fidelity flux tube gyrokinetic GENE simulations and consi ...

The desire and ability to place AI-enabled applications on the edge has grown significantly in recent years. However, the compute-, area-, and power-constrained nature of edge devices are stressed by the needs of the AI-enabled applications, due to a gener ...

Carbon impurity transport is studied in the TCV tokamak using a charge exchange recombination diagnostic. TCVs flexible shaping capabilities were exploited to extend previous impurity transport studies to negative triangularity (delta < 0). A practical way ...

Plasmas with negative triangularity (NT) shape have been recently shown to be able to achieve H-mode levels of confinement in L-mode, avoiding detrimental edge localised modes. Therefore, this plasma geometry is now studied as a possible viable option for ...

The accurate, robust and efficient transfer of the deformation gradient tensor between meshes of different resolution is crucial in cardiac electromechanics simulations. This paper presents a novel method that combines rescaled localized Radial Basis Funct ...

This paper studies kernel ridge regression in high dimensions under covariate shifts and analyzes the role of importance re-weighting. We first derive the asymptotic expansion of high dimensional kernels under covariate shifts. By a bias-variance decomposi ...

Single-photon 3D cameras can record the time-of-arrival of billions of photons per second with picosecond accuracy. One common approach to summarize the photon data stream is to build a per-pixel timestamp histogram, resulting in a 3D histogram tensor that ...

In this thesis we study how physical principles imposed on the S-matrix, such as Lorentz invariance, unitarity, crossing symmetry and analyticity constrain quantum field theories at the nonperturbative level. We start with a pedagogical introduction to the ...

We expand Hilbert series technologies in effective field theory for the inclusion of massive particles, enabling, among other things, the enumeration of operator bases for non-linearly realized gauge theories. We find that the Higgs mechanism is manifest a ...

Polar Codes: Characterization of Exponent, Bounds, and Constructions

Chat with Graph Search

Overcoming Distribution Shifts and Imbalance Challenges in Representation Learning for Deep Regression Models

SPEEDING UP KRYLOV SUBSPACE METHODS FOR COMPUTING f(A)b VIA RANDOMIZATION

Randomized methods for computing joint eigenvalues, with applications to multiparameter eigenvalue problems and root finding

Mass lumping the dual cell method to arbitrary polynomial degree for acoustic and electromagnetic waves

Accelerator-driven Data Arrangement to Minimize Transformers Run-time on Multi-core Architectures

Randomized low-rank approximation and its applications

The Power of Two Matrices in Spectral Algorithms for Community Recovery

First-principles thermodynamics of precipitation in aluminum-containing refractory alloys

Spectral Estimators for High-Dimensional Matrix Inference

RANDOMIZED JOINT DIAGONALIZATION OF SYMMETRIC

Experiments and gyrokinetic simulations of TCV plasmas with negative triangularity in view of DTT operations

Physical insights from the aspect ratio dependence of turbulence in negative triangularity plasmas

Exploring High-Performance and Energy-Efficient Architectures for Edge AI-Enabled Applications

Study of impurity C transport and plasma rotation in negative triangularity on the TCV tokamak

First-principle based predictions of the effects of negative triangularity on DTT scenarios

Preserving the positivity of the deformation gradient determinant in intergrid interpolation by combining RBFs and SVD: Application to cardiac electromechanics

High-Dimensional Kernel Methods under Covariate Shift: Data-Dependent Implicit Regularization

Learned Compressive Representations for Single-Photon 3D Imaging

Nonperturbative aspects of scattering amplitudes

Hilbert series, the Higgs mechanism, and HEFT