Zobrazeno 1 - 10
of 53 182
pro vyhledávání: '"Kernel methods"'
Increasing the angular resolution of an interferometric array requires placing its elements at large separations. This often leads to sparse coverage and introduces challenges to reconstructing images from interferometric data. We introduce a new int
Externí odkaz:
http://arxiv.org/abs/2412.01908
Quantum machine learning is considered one of the current research fields with immense potential. In recent years, Havl\'i\v{c}ek et al. [Nature 567, 209-212 (2019)] have proposed a quantum machine learning algorithm with quantum-enhanced feature spa
Externí odkaz:
http://arxiv.org/abs/2411.02913
Autor:
Kleikamp, Hendrik, Wenzel, Tizian
In this contribution, kernel approximations are applied as ansatz functions within the Deep Ritz method. This allows to approximate weak solutions of elliptic partial differential equations with weak enforcement of boundary conditions using Nitsche's
Externí odkaz:
http://arxiv.org/abs/2410.03503
We study the kernel instrumental variable algorithm of \citet{singh2019kernel}, a nonparametric two-stage least squares (2SLS) procedure which has demonstrated strong empirical performance. We provide a convergence analysis that covers both the ident
Externí odkaz:
http://arxiv.org/abs/2411.19653
Autor:
Miroszewski, Artur, Asiani, Marco Fellous, Mielczarek, Jakub, Saux, Bertrand Le, Nalepa, Jakub
Quantum Machine Learning (QML) has gathered significant attention through approaches like Quantum Kernel Machines. While these methods hold considerable promise, their quantum nature presents inherent challenges. One major challenge is the limited re
Externí odkaz:
http://arxiv.org/abs/2407.15776