Zobrazeno 1 - 10
of 299
pro vyhledávání: '"Pakman A"'
Autor:
Cohen, Yarden, Navarro, Alexandre Khae Wu, Frellsen, Jes, Turner, Richard E., Riemer, Raziel, Pakman, Ari
The need for regression models to predict circular values arises in many scientific fields. In this work we explore a family of expressive and interpretable distributions over circle-valued random functions related to Gaussian processes targeting two
Externí odkaz:
http://arxiv.org/abs/2406.13151
Autor:
Pakman, Ari
Publikováno v:
Applied Mathematics Letters, Volume 159, January 2025, 109284
Markov Chain Monte Carlo algorithms, the method of choice to sample from generic high-dimensional distributions, are rarely used for continuous one-dimensional distributions, for which more effective approaches are usually available (e.g. rejection s
Externí odkaz:
http://arxiv.org/abs/2312.16546
Publikováno v:
In Materialia December 2024 38
Autor:
Pakman, Ari
Publikováno v:
In Applied Mathematics Letters January 2025 159
Publikováno v:
In Vacuum August 2024 226
Probability density models based on deep networks have achieved remarkable success in modeling complex high-dimensional datasets. However, unlike kernel density estimators, modern neural models do not yield marginals or conditionals in closed form, a
Externí odkaz:
http://arxiv.org/abs/2106.04741
Autor:
Pakman, Ari, Nejatbakhsh, Amin, Gilboa, Dar, Makkeh, Abdullah, Mazzucato, Luca, Wibral, Michael, Schneidman, Elad
Publikováno v:
NeurIPS 2021
The integration and transfer of information from multiple sources to multiple targets is a core motive of neural systems. The emerging field of partial information decomposition (PID) provides a novel information-theoretic lens into these mechanisms
Externí odkaz:
http://arxiv.org/abs/2102.00218
Autor:
Wang, Yueqi, Lee, Yoonho, Basu, Pallab, Lee, Juho, Teh, Yee Whye, Paninski, Liam, Pakman, Ari
Learning community structures in graphs has broad applications across scientific domains. While graph neural networks (GNNs) have been successful in encoding graph structures, existing GNN-based methods for community detection are limited by requirin
Externí odkaz:
http://arxiv.org/abs/2010.15727
Publikováno v:
In Journal of Alloys and Compounds 15 October 2023 960
Publikováno v:
In Surface & Coatings Technology 15 July 2023 464