Results 161 to 170 of about 11,206 (199)

Cognitive architecture and behavioral model based on social evidence and resource constraints. [PDF]

Brain Inform
Kolonin A.
europepmc   +1 more source

A clustering method for single-cell RNA sequencing data based on denoising and masking learning. [PDF]

Front Bioinform
Xu S, Yan W, Zhang B, Qi H, Wang K.
europepmc   +1 more source

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Kernel density matrices for probabilistic deep learning

Quantum Machine Intelligence, 2023
This paper introduces a novel approach to probabilistic deep learning, kernel density matrices, which provide a simpler yet effective mechanism for representing joint probability distributions of both continuous and discrete random variables.
Fabio A. Gonz'alez, Ra'ul Ramos-Poll'an, Joseph A. Gallego-Mejia   +2 more
semanticscholar   +1 more source

Models of Random Sparse Eigenmatrices and Bayesian Analysis of Multivariate Structure

, 2016
We discuss probabilistic models of random covariance structures defined by distributions over sparse eigenmatrices. The decomposition of orthogonal matrices in terms of Givens rotations defines a natural, interpretable framework for defining ...
Andrew Cron, M. West
semanticscholar   +1 more source

Nonparametric probabilistic approach of uncertainties with correlated mass and stiffness random matrices

Mechanical systems and signal processing, 2018
This paper concerns the probabilistic modeling of uncertainties in structural dynamics. For real complex structures, the accurate modeling and identification of uncertainties is challenging due to the large number of involved uncertain parameters.
A. Batou, A. Nabarrete
semanticscholar   +1 more source

Scaling Probabilistic Circuits via Monarch Matrices

International Conference on Machine Learning
Probabilistic Circuits (PCs) are tractable representations of probability distributions allowing for exact and efficient computation of likelihoods and marginals.
Honghua Zhang, Meihua Dang, Benjie Wang, Stefano Ermon, Nanyun Peng, Guy Van den Broeck   +5 more
semanticscholar   +1 more source

Interaction-correlated random matrices

Physical review B
We introduce a family of random matrices where correlations between matrix elements are induced via interaction-derived Boltzmann factors. Varying these yields access to different ensembles.
A. Saberi, Sina Saber, R. Moessner
semanticscholar   +1 more source

Probabilistic cellular automata with local transition matrices: Synchronization, ergodicity, and inference

Bernoulli
We introduce a new class of probabilistic cellular automata that are capable of exhibiting rich dynamics such as synchronization and ergodicity and can be easily inferred from data.
Erhan Bayraktar, Fei Lu, Mauro Maggioni, Ruoyu Wu, Sichen Yang   +4 more
semanticscholar   +1 more source

Quantum systems from random probabilistic automata

Physical Review A
Probabilistic cellular automata with deterministic updating are quantum systems. We employ the quantum formalism for an investigation of random probabilistic cellular automata, which start with a probability distribution over initial configurations.
A. Kreuzkamp, C. Wetterich
semanticscholar   +1 more source