22 papers · ranked by Valyu relevance
Joe Suzuki, Yusuke Inaoka
This paper considers an extension of the linear non-Gaussian acyclic model (LiNGAM) that determines the causal order among variables from a dataset when the variables are expressed by a set of linear equations, including noise. In particular, we assume that the variables are binary. The existing LiNGAM assumes that no…
Purushottam D. Dixit
In modern biological physics, there is a great interest in building generative probabilistic models for ensembles of covarying binary variables. A popular approach is to use the maximum entropy principle. Here, one builds generative models that use as constraints lower level statistics estimated from the data. While…
Dana Kovaleva, O. Yu. Malkov, P. V. Kaygorodov
The BDB, Binary star DataBase http://bdb.inasan.ru combines data of the catalogues of binary and multiple stars of all observational types. There is a number of ways for variable stars to form or to be a part of binary or multiple systems. We describe how such stars are represented in the database.
Natchalee Srimaneekarn, Anthony Hayter, Wei Liu, Chanita Tantipoj
Multivariate analysis with binary response is extensively utilized in dental research due to variations in dichotomous outcomes. One of the analyses for binary response variable is binary logistic regression, which explores the associated factors and predicts the response probability of the binary variable. This…
Takashi Arai
We propose a probability distribution for multivariate binary random variables. For this purpose, we use the Grassmann number, an anti-commuting number. In our model, the partition function, the central moment, and the marginal and conditional distributions are expressed analytically by the matrix of the parameters…
Kyungmin Lim, Su-Young Kim
In the structural equation modeling framework, binary variable models are generally considered a special case of ordinal variable models, as both involve similar scale assignment processes. However, the scaling processes of the two model types differ, with these differences becoming increasingly pronounced in the…
David M. Danks, Clark Glymour
Linear models have special advantages for model search and for the estimation of causal effects, several of which are listed in the Abstract. Property ( 1) permits the detection of common causes via the Tetrad Representation Theorem, and in combination with properties (3) and (4) is sufficient for the determination of…
András Telcs, Raúl Alcaraz
We develop a finite-resolution empirical framework for applying nonnegative Mages-Anastasiadi-Rohner partial information decomposition (MAR-PID) to continuous and non-binary discrete variables. The variables are represented by recursive quantile binarization. This provides a balanced binary-tree representation at each…
Theo Knijnenburg, Gunnar Klau, Francesco Iorio, Mathew Garnett + 3 more
Mining large datasets using machine learning approaches often leads to models that are hard to interpret and not amenable to the generation of hypotheses that can be experimentally tested. Finding ‘actionable knowledge’ is becoming more important, but also more challenging as datasets grow in size and complexity. We…
Ajay Subbaroyan, Olivier C. Martin, Areejit Samal
The properties of random Boolean networks as models of gene regulation have been investigated extensively by the statistical physics community. In the past two decades, there has been a dramatic increase in the reconstruction and analysis of Boolean models of biological networks. In such models, neither network…
Yuki Furue, Makiko Konoshima, Hirotaka Tamura, Jun Ohkubo
Annealing machines specialized for combinatorial optimization problems have been developed, and some companies offer services to use those machines. Such specialized machines can only handle binary variables, and their input format is the quadratic unconstrained binary optimization (QUBO) formulation. Therefore…
Maryam Sadiq, Nasser A. Alsadhan, Ramla Shah, Sidra Younas + 2 more
'Zahid Rasheed' 'Suyan Tian'] Variable selection methods are very popular, especially in the field of big data with large predictors. These procedures improve the accuracy and performance of the model by eliminating irrelevant and redundant variables. The main contribution of this study is to couple a logit model with…
Vita Ratnasari, Purhadi, Marisa Rifada, Andrea Tri Rian Dani
Logit regression (or logistic regression) is a statistical analysis of categorical data. The binary responses have two categories. We present the Bivariate Polynomial Binary Logit Regression (BPBLR), which extends logit regression by modeling two correlated binary response variables. This model uses a polynomial…
Guilherme C.P. Innocentini, Sarah Guiziou, Jerome Bonnet, Ovidiu Radulescu
We propose an analytic solution for the stochastic dynamics of a binary biological switch, defined as a DNA unit with two mutually exclusive configurations, each one triggering the expression of a different gene. Such a device could be used as a memory unit for biological computing systems designed to operate in noisy…
Zeinab Mohammadi, Zoe C. Ashwood, Jonathan W. Pillow
Recent work has revealed that mice do not rely on a stable strategy during perceptual decision-making, but switch between multiple strategies within a single session [1, 2]. However, this switching behavior has not yet been characterized in non-stationary environments, and the factors that govern switching remain…
Xiaowei Wu, Hongxiao Zhu
We propose a new approach to test associations between binary trees and covariates. In this approach, binary-tree structured data are treated as sample paths of binary fission Markov branching processes (bMBP). We propose a generalized linear regression model and developed inference procedures for association testing…
Suchetana Mitra, Priyotosh Sil, Ajay Subbaroyan, Olivier C. Martin + 1 more
Boolean networks (BNs) have been extensively used to model the dynamics of gene regulatory networks (GRNs) that underlie cellular decisions. The dynamics of BNs depend on the network architecture and regulatory logic rules (or Boolean functions (BFs)) associated with nodes, both of which have been shown to be far from…
Ibragim E. Suleimenov, Yelizaveta S. Vitulyova, Sherniyaz B. Kabdushev, Akhat S. Bakirov
'Sherniyaz B. Kabdushev' 'Akhat S. Bakirov'] Multivalued logics are becoming one of the most important tools of information technology. They are in great demand for creation of artificial intelligence systems that are close to human intelligence, since the functioning of the latter cannot be reduced to the operations…
Ernst D. Berg
Dynamic Unary Encoding takes Unary Encoding to the next level. Every n-bit binary string is an encoding of dynamic unary and every n-bit binary string is encodable by dynamic unary. By utilizing both forms of unary code and a single bit of parity information dynamic unary encoding partitions 2 n non-negative integers…
Authors not listed
Protein-protein interactions (PPIs) play an essential role in biological processes. Molecules that stabilize or induce PPIs in ternary complexes have received growing attention for their therapeutic potential in engaging ’undruggable’ targets and their high selectivity. Here, we investigate the kinetics and thermody-…
Arno Onken, Jue Xie, Stefano Panzeri, Camillo Padoa-Schioppa
A fundamental and recurrent question in systems neuroscience is that of assessing what variables are encoded by a given population of neurons. Such assessments are often challenging because neurons in one brain area may encode multiple variables, and because neuronal representations might be categorical (different…
Yalin Li, John Trimmer, Steven Hand, Xinyi Zhang + 6 more
The pursuit of sustainability has catalyzed broad investment in the research, development, and deployment (RD&D) of innovative water, sanitation, and resource recovery technologies, yet the lack of transparent and agile methodologies to navigate the expansive landscape of technology development pathways remains a…