Zobrazeno 1 - 10
of 23 662
pro vyhledávání: '"A. Márton"'
We conduct a comprehensive study of anomalous charge transport in the quantum sine--Gordon model. Employing the framework of Generalized Hydrodynamics, we compute Drude weights and Onsager matrices across a wide range of coupling strengths to quantif
Externí odkaz:
http://arxiv.org/abs/2411.11473
In this survey, we discuss volumetric and combinatorial results concerning (mostly finite) intersections or unions of balls (mostly of equal radii) in the $d$-dimensional real vector space, mostly equipped with the Euclidean norm. Our first topic is
Externí odkaz:
http://arxiv.org/abs/2411.10302
Employing pre-trained Large Language Models (LLMs) has become the de facto standard in Natural Language Processing (NLP) despite their extensive data requirements. Motivated by the recent surge in research focused on training LLMs with limited data,
Externí odkaz:
http://arxiv.org/abs/2411.09539
Autor:
Trencséni, Márton
This paper examines the use of Monte Carlo simulations to understand statistical concepts in A/B testing and Randomized Controlled Trials (RCTs). We discuss the applicability of simulations in understanding false positive rates and estimate statistic
Externí odkaz:
http://arxiv.org/abs/2411.06701
Autor:
Berrada, Tariq, Astolfi, Pietro, Verbeek, Jakob, Hall, Melissa, Havasi, Marton, Drozdzal, Michal, Benchetrit, Yohann, Romero-Soriano, Adriana, Alahari, Karteek
Latent diffusion models (LDMs) power state-of-the-art high-resolution generative image models. LDMs learn the data distribution in the latent space of an autoencoder (AE) and produce images by mapping the generated latents into RGB image space using
Externí odkaz:
http://arxiv.org/abs/2411.04873
Autor:
Ifriqi, Tariq Berrada, Astolfi, Pietro, Hall, Melissa, Askari-Hemmat, Reyhane, Benchetrit, Yohann, Havasi, Marton, Muckley, Matthew, Alahari, Karteek, Romero-Soriano, Adriana, Verbeek, Jakob, Drozdzal, Michal
Large-scale training of latent diffusion models (LDMs) has enabled unprecedented quality in image generation. However, the key components of the best performing LDM training recipes are oftentimes not available to the research community, preventing a
Externí odkaz:
http://arxiv.org/abs/2411.03177
The accurate modeling of individual movement in cities has significant implications for policy decisions across various sectors. Existing research emphasizes the universality of human mobility, positing that simple models can capture population-level
Externí odkaz:
http://arxiv.org/abs/2410.23502
Autor:
Kiss, Csaba, Müller, Thomas G., Farkas-Takács, Anikó, Moór, Attila, Protopapa, Silvia, Parker, Alex H., Santos-Sanz, Pablo, Ortiz, Jose Luis, Holler, Bryan J., Wong, Ian, Stansberry, John, Fernández-Valenzuela, Estela, Glein, Christopher R., Lellouch, Emmanuel, Vilenius, Esa, Kalup, Csilla E., Regály, Zsolt, Szakáts, Róbert, Marton, Gábor, Pál, András, Szabó, Gyula M.
We report on the discovery of a very prominent mid-infrared (18-25 {\mu}m) excess associated with the trans-Neptunian dwarf planet (136472) Makemake. The excess, detected by the MIRI instrument of the James Webb Space Telescope, along with previous m
Externí odkaz:
http://arxiv.org/abs/2410.22544
Behavioral adoptions are influenced by peers in different ways. While some individuals may change after a single incoming influence, others need multiple cumulated attempts. These two mechanism, known as the simple and the complex contagions, often o
Externí odkaz:
http://arxiv.org/abs/2410.22115
Autor:
Holderrieth, Peter, Havasi, Marton, Yim, Jason, Shaul, Neta, Gat, Itai, Jaakkola, Tommi, Karrer, Brian, Chen, Ricky T. Q., Lipman, Yaron
We introduce generator matching, a modality-agnostic framework for generative modeling using arbitrary Markov processes. Generators characterize the infinitesimal evolution of a Markov process, which we leverage for generative modeling in a similar v
Externí odkaz:
http://arxiv.org/abs/2410.20587