Zobrazeno 1 - 10
of 4 358
pro vyhledávání: '"P. Aarts"'
Autor:
Fiorio, Luan Vinícius, Karanov, Boris, Defraene, Bruno, David, Johan, van Houtum, Wim, Widdershoven, Frans, Aarts, Ronald M.
We propose and analyze the use of an explicit time-context window for neural network-based spectral masking speech enhancement to leverage signal context dependencies between neighboring frames. In particular, we concentrate on soft masking and loss
Externí odkaz:
http://arxiv.org/abs/2408.15582
Autor:
K. R. van Straalen, K. Dudink, P. Aarts, H. H. van der Zee, T. P. P. van den Bosch, J. Giang, E. P. Prens, J. Damman
Publikováno v:
Frontiers in Immunology, Vol 13 (2022)
Hidradenitis suppurativa (HS) is a chronic auto-inflammatory skin disease with a complex and multifactorial pathogenesis involving both the innate and adaptive immune system. Despite limited evidence for local complement activation, conflicting resul
Externí odkaz:
https://doaj.org/article/1acdc2ad48b246f181fa11c15463d789
We demonstrate that the update of weight matrices in learning algorithms can be described in the framework of Dyson Brownian motion, thereby inheriting many features of random matrix theory. We relate the level of stochasticity to the ratio of the le
Externí odkaz:
http://arxiv.org/abs/2407.16427
Autor:
Yao, Junxiang, Aarts, Jan
Superconducting junctions with a ferromagnet as the weak link, where triplet correlations can transport supercurrents over a substantial distance, have been of long-standing interest. In this work, we study the triplet transport in planar La$_{0.7}$S
Externí odkaz:
http://arxiv.org/abs/2404.15969
Autor:
Moraga, S. Mildiner, Aarts, E.
Hidden Markov models (HMMs) are probabilistic methods in which observations are seen as realizations of a latent Markov process with discrete states that switch over time. Moving beyond standard statistical tests, HMMs offer a statistical environment
Externí odkaz:
http://arxiv.org/abs/2403.12561
Autor:
Deblais, Antoine, Xie, Kaili, Lewin-Jones, Peter, Aarts, Dirk, Herrada, Miguel A., Eggers, Jens, Sprittles, James E., Bonn, Daniel
Despite the large body of research on coalescence, firm agreement between experiment, theory, and computation has not been established for the very earliest times following the initial contact of two liquid volumes. Combining a range of experimental
Externí odkaz:
http://arxiv.org/abs/2402.00500
Autor:
Bignell, Ryan, Aarts, Gert, Allton, Chris, Anwar, M. Naeem, Burns, Timothy J., Jäger, Benjamin, Skullerud, Jon-Ivar
Reconstructed-correlator methods have been used to investigate thermal effects in mesonic correlation functions in a fit-independent manner. This technique has recently been extended to the baryonic sector. In this work different ways of implementing
Externí odkaz:
http://arxiv.org/abs/2312.03560
This study delves into the connection between machine learning and lattice field theory by linking generative diffusion models (DMs) with stochastic quantization, from a stochastic differential equation perspective. We show that DMs can be conceptual
Externí odkaz:
http://arxiv.org/abs/2311.03578
In this work, we establish a direct connection between generative diffusion models (DMs) and stochastic quantization (SQ). The DM is realized by approximating the reversal of a stochastic process dictated by the Langevin equation, generating samples
Externí odkaz:
http://arxiv.org/abs/2309.17082
We consider the problem of fairly allocating the cost of providing a service among a set of users, where the service cost is formulated by an NP-hard {\it covering integer program (CIP)}. The central issue is to determine a cost allocation to each us
Externí odkaz:
http://arxiv.org/abs/2309.16914