Results 51 to 60 of about 169,073 (281)
Partially observed Markov random fields are variable neighborhood random fields
The present paper has two goals. First to present a natural example of a new class of random fields which are the variable neighborhood random fields. The example we consider is a partially observed nearest neighbor binary Markov random field. The second
Cassandro, Marzio +2 more
core +1 more source
Stable Imitation of Multigait and Bipedal Motions for Quadrupedal Robots Over Uneven Terrains
How are quadrupedal robots empowered to execute complex navigation tasks, including multigait and bipedal motions? Challenges in stability and real‐world adaptation persist, especially with uneven terrains and disturbances. This article presents an imitation learning framework that enhances adaptability and robustness by incorporating long short‐term ...
Erdong Xiao +3 more
wiley +1 more source
Atherosclerosis, a leading cause of cardiovascular disease, necessitates advanced and innovative modeling techniques to better understand and predict plaque dynamics.
Amun G. Hofmann
doaj +1 more source
Learning Traffic Flow Dynamics Using Random Fields
This paper presents a mesoscopic traffic flow model that explicitly describes the spatio-temporal evolution of the probability distributions of vehicle trajectories.
Saif Eddin G. Jabari +3 more
doaj +1 more source
Generalisation of the Hammersley-Clifford Theorem on Bipartite Graphs [PDF]
The Hammersley-Clifford theorem states that if the support of a Markov random field has a safe symbol then it is a Gibbs state with some nearest neighbour interaction.
Chandgotia, Nishant
core
This study performs pan‐viromic profiling of 14,529 samples from 5,710 domestic herbivores across five Chinese provinces, establishing the DhCN‐Virome (1,085,360 viral metagenomes). It reveals species/sample‐specific viromic signatures and cross‐species transmission dynamics, aiding unified disease control.
Yue Sun +19 more
wiley +1 more source
Bayesian Parameter Estimation for Latent Markov Random Fields and Social Networks [PDF]
Undirected graphical models are widely used in statistics, physics and machine vision. However Bayesian parameter estimation for undirected models is extremely challenging, since evaluation of the posterior typically involves the calculation of an ...
Andrieu C. +30 more
core +3 more sources
Identifying Cytokine Motif‐Containing, Immunomodulatory Bacterial Proteins in Human Gut Microbiome
By building and constructing HMM (Upper left, blue), the authors identify CMCPs in bacteria genomes and CRC related metagenomes and enriched CRC‐related CMCPs (Upper right, blue). They analyze sequence and structural similarity of hits (Lower left, green), test function with engineered EcN delivered to tumors in a mouse tumor model (Lower right, pink ...
Ziyu Wang +12 more
wiley +1 more source
Minimum Conditional Description Length Estimation for Markov Random Fields
In this paper we discuss a method, which we call Minimum Conditional Description Length (MCDL), for estimating the parameters of a subset of sites within a Markov random field. We assume that the edges are known for the entire graph $G=(V,E)$.
Neuhoff, David L., Reyes, Matthew G.
core +1 more source
Protein complexes like KIBRA‐PKMζ are crucial for maintaining memories, forming month‐long protein traces in memory‐tagged neurons, but conventional RNA‐seq analysis fails to detect their transcript changes, leaving memory molecules undetected in the shadows of abundantly‐expressed genes.
Jiyeon Han +10 more
wiley +1 more source

