Results 81 to 90 of about 68,993 (274)
Consistent Second-Order Conic Integer Programming for Learning Bayesian Networks
, 2020 Bayesian Networks (BNs) represent conditional probability relations among a set of random variables (nodes) in the form of a directed acyclic graph (DAG), and have found diverse applications in knowledge discovery.
Kucukyavuz, Simge +3 more
core
Gaussian Process Structural Equation Models with Latent Variables [PDF]
, 2010 In a variety of disciplines such as social sciences, psychology, medicine and economics, the recorded data are considered to be noisy measurements of latent variables connected by some causal structure.
Gramacy, Robert B., Silva, Ricardo
core +1 more source
Advanced Robotics Research, EarlyView.An introduction for multidrive and environment‐adaptive micro/nanorobotics: design and fabrication strategies, intelligent actuation, and their applications. Various intelligent actuation approaches—magnetic, acoustic, optical, chemical, and biological—can be synergistically designed to enhance flexibility and adaptive behavior for precision medicine ...
Aiqing Ma +10 more
wiley +1 more source
Hierarchical Summary Statistics Encoding Across Primary Visual and Posterior Parietal Cortices
Advanced Science, EarlyView.This study shows that mouse V1 simultaneously encodes the ensemble mean and variance of motion, providing a robust summary‐statistic representation that persists despite single‐neuron variability. These signals propagate to PPC, where they are transformed into abstract category representations during decision making.
Young‐Beom Lee +4 more
wiley +1 more source
Advanced Science, EarlyView.Skeleton‐oriented object segmentation (SKOOTS) introduces a new strategy for 3D mitochondrial instance segmentation by predicting explicit skeletons rather than relying on boundary cues. This approach enables robust analysis of densely packed organelles in large FIB‐SEM datasets.
Christopher J. Buswinka +3 more
wiley +1 more source
Inference of gene regulatory networks from genetic perturbations with linear regression model. [PDF]
PLoS ONE, 2013 It is an effective strategy to use both genetic perturbation data and gene expression data to infer regulatory networks that aims to improve the detection accuracy of the regulatory relationships among genes.
Zijian Dong, Tiecheng Song, Chuang Yuan
doaj +1 more source
Customizing Tactile Sensors via Machine Learning‐Driven Inverse Design
Advanced Science, EarlyView.ABSTRACT Replicating the sophisticated sense of touch in artificial systems requires tactile sensors with precisely tailored properties. However, manually navigating the complex microstructure‐property relationship results in inefficient and suboptimal designs.
Baocheng Wang +15 more
wiley +1 more source
A Classical and Bayesian Approach for Parameter Estimation in Structural Equation Models
Journal of New Theory, 2020 Structural Equation Models (SEMs) with latent variables provide a general framework for modelling relationships in multivariate data. Although SEMs are most commonly used in studies involving intrinsically latent variables, such as happiness, quality of ...
Naci Murat, Mehmet Ali Cengiz
doaj
Relationship between haemodynamic indicators and haemogram in patients with heart failure
ESC Heart Failure, 2023 Aims Pulmonary congestion, reduced cardiac output, neurohumoral factor activation, and decreased renal function associated with decreased cardiac function may have various effects on haemograms.
Takuya Oh +6 more
doaj +1 more source
Emerging Memory and Device Technologies for Hardware‐Accelerated Model Training and Inference
Advanced Electronic Materials, EarlyView.This review investigates the suitability of various emerging memory technologies as compute‐in‐memory hardware for artificial intelligence (AI) applications. Distinct requirements for training‐ and inference‐centric computing are discussed, spanning device physics, materials, and system integration.
Yoonho Cho +6 more
wiley +1 more source