Results 91 to 100 of about 151,404 (250)

Identification of Pattern Completion Neurons in Neuronal Ensembles Using Probabilistic Graphical Models. [PDF]

J Neurosci, 2021
Carrillo-Reid L, Han S, O'Neil D, O'Neil D, Taralova E, Jebara T, Yuste R.   +6 more
europepmc   +1 more source

Distributed Parameter Estimation in Probabilistic Graphical Models

, 2014
This paper presents foundational theoretical results on distributed parameter estimation for undirected probabilistic graphical models. It introduces a general condition on composite likelihood decompositions of these models which guarantees the global ...
de Freitas, Nando, Denil, Misha, Mizrahi, Yariv Dror   +2 more
core  

Double Helical Plasmonic Antennas

Advanced Functional Materials, EarlyView.
Plasmonic double helical antennas funnel circularly polarized light to the nanoscale, offering strong chiroptical interaction and directional light emission. Extending a single helix design tool, this study combines numerical modeling with experimental validation, revealing large, broadband dissymmetry factors in the visible range.
Aleksei Tsarapkin, Luka Zurak, Krzysztof Maćkosz, Lorenz Löffler, Victor Deinhart, Ivo Utke, Thorsten Feichtner, Katja Höflich   +7 more
wiley   +1 more source

Defect‐Mediated Scintillation in Fully Inorganic Perovskites via Water‐Induced 0D/3D Phase Modulation

Advanced Functional Materials, EarlyView.
A reproducible synthesis to control 3D/0D phase ratios via water‐tuned solvent–antisolvent methods is presented. Enhanced scintillation yield and ultrafast decay are achieved. Defect‐driven emission mechanisms are revealed through cathodoluminescence and radioluminescence, shedding light on the underexplored role of the 0D Cs4PbBr6 and mixed 0D/3D ...
Mario Calora, Francesco Carulli, Nadir Vanni, Antonella Giuri, Elena Ferrari, Matteo Masino, Laura Lazzarini, Francesca Rossi, Gianluca Accorsi, Anna Moliterni, Davide Altamura, Cinzia Giannini, Luca Cappelletti, Gianluca Quarta, Alberto Quaranta, Rosanna Mastria, Anna Paola Caricato, Sergio Brovelli, Aurora Rizzo   +18 more
wiley   +1 more source

Toward Variational Structural Learning of Bayesian Networks

IEEE Access
This study presents a novel variational framework for structural learning in Bayesian networks (BNs), addressing the key limitation of existing Bayesian methods: their lack of scalability to large graphs with many variables.
Andres R. Masegosa, Manuel Gomez-Olmedo
doaj   +1 more source

Prediction of short-term antidepressant response using probabilistic graphical models with replication across multiple drugs and treatment settings. [PDF]

Neuropsychopharmacology, 2021
Athreya AP, Brückl T, Binder EB, John Rush A, Biernacka J, Frye MA, Neavin D, Skime M, Monrad D, Iyer RK, Mayes T, Trivedi M, Carter RE, Wang L, Weinshilboum RM, Croarkin PE, Bobo WV.   +16 more
europepmc   +1 more source

Verbalized Probabilistic Graphical Modeling

Human cognition excels at transcending sensory input and forming latent representations that structure our understanding of the world. Although Large Language Models (LLMs) can produce chain-of-thought reasoning, they lack a principled framework to capture latent structures and model uncertainty, especially in compositional reasoning tasks.
Huang, Hengguan, Shen, Xing, Wang, Songtao, Meng, Lingfa, Liu, Dianbo, Wang, Hao, Bhatt, Samir   +6 more
openaire   +2 more sources

MOFs and COFs in Electronics: Bridging the Gap between Intrinsic Properties and Measured Performance

Advanced Functional Materials, EarlyView.
Metal‐organic frameworks (MOFs) and covalent organic frameworks (COFs) hold promise for advanced electronics. However, discrepancies in reported electrical conductivities highlight the importance of measurement methodologies. This review explores intrinsic charge transport mechanisms and extrinsic factors influencing performance, and critically ...
Jonas F. Pöhls, R. Thomas Weitz
wiley   +1 more source

Digital Discovery of Synthesizable Metal−Organic Frameworks via Molecular Dynamics‑Informed, High‑Fidelity Deep Learning

Advanced Functional Materials, EarlyView.
Tabular foundation model interrogates the synthetic likelihood of metal−organic frameworks. Abstract Metal–organic frameworks (MOFs) are celebrated for their chemical and structural versatility, and in‑silico screening has significantly accelerated their discovery; yet most hypothetical MOFs (hMOFs) never reach the bench because their synthetic ...
Xiaoyu Wu, Rui Zheng, Quan Liu, Jianwen Jiang   +3 more
wiley   +1 more source

The Libra Toolkit for Probabilistic Models

, 2015
The Libra Toolkit is a collection of algorithms for learning and inference with discrete probabilistic models, including Bayesian networks, Markov networks, dependency networks, and sum-product networks. Compared to other toolkits, Libra places a greater
Lowd, Daniel, Rooshenas, Amirmohammad
core