Zobrazeno 1 - 10
of 6 734
pro vyhledávání: '"A. Donatelli"'
Autor:
Donatelli, Marco, Furchì, Davide
The iterated Arnoldi-Tikhonov (iAT) method is a regularization technique particularly suited for solving large-scale ill-posed linear inverse problems. Indeed, it reduces the computational complexity through the projection of the discretized problem
Externí odkaz:
http://arxiv.org/abs/2404.08321
Autor:
Mughal, Muhammad Hamza, Dabral, Rishabh, Habibie, Ikhsanul, Donatelli, Lucia, Habermann, Marc, Theobalt, Christian
Gestures play a key role in human communication. Recent methods for co-speech gesture generation, while managing to generate beat-aligned motions, struggle generating gestures that are semantically aligned with the utterance. Compared to beat gesture
Externí odkaz:
http://arxiv.org/abs/2403.17936
In the past decades, a remarkable amount of research has been carried out regarding fast solvers for large linear systems resulting from various discretizations of fractional differential equations (FDEs). In the current work, we focus on multigrid m
Externí odkaz:
http://arxiv.org/abs/2403.16352
We consider an unsupervised bilevel optimization strategy for learning regularization parameters in the context of imaging inverse problems in the presence of additive white Gaussian noise. Compared to supervised and semi-supervised metrics relying e
Externí odkaz:
http://arxiv.org/abs/2403.07026
We present novel improvements in the context of symbol-based multigrid procedures for solving large block structured linear systems. We study the application of an aggregation-based grid transfer operator that transforms the symbol of a block Toeplit
Externí odkaz:
http://arxiv.org/abs/2403.02139
Autor:
Bianchi, Davide, Evangelista, Davide, Aleotti, Stefano, Donatelli, Marco, Piccolomini, Elena Loli, Li, Wenbin
We investigate a variational method for ill-posed problems, named $\texttt{graphLa+}\Psi$, which embeds a graph Laplacian operator in the regularization term. The novelty of this method lies in constructing the graph Laplacian based on a preliminary
Externí odkaz:
http://arxiv.org/abs/2312.16936
We present the Granular AMR Parsing Evaluation Suite (GrAPES), a challenge set for Abstract Meaning Representation (AMR) parsing with accompanying evaluation metrics. AMR parsers now obtain high scores on the standard AMR evaluation metric Smatch, cl
Externí odkaz:
http://arxiv.org/abs/2312.03480
The Arnoldi-Tikhonov method is a well-established regularization technique for solving large-scale ill-posed linear inverse problems. This method leverages the Arnoldi decomposition to reduce computational complexity by projecting the discretized pro
Externí odkaz:
http://arxiv.org/abs/2311.11823
Autor:
Cao, Yong, Kementchedjhieva, Yova, Cui, Ruixiang, Karamolegkou, Antonia, Zhou, Li, Dare, Megan, Donatelli, Lucia, Hershcovich, Daniel
Building upon the considerable advances in Large Language Models (LLMs), we are now equipped to address more sophisticated tasks demanding a nuanced understanding of cross-cultural contexts. A key example is recipe adaptation, which goes beyond simpl
Externí odkaz:
http://arxiv.org/abs/2310.17353
The goal of compositional generalization benchmarks is to evaluate how well models generalize to new complex linguistic expressions. Existing benchmarks often focus on lexical generalization, the interpretation of novel lexical items in syntactic str
Externí odkaz:
http://arxiv.org/abs/2310.15040