Results 81 to 90 of about 21,998,513 (385)

STDP Installs in Winner-Take-All Circuits an Online Approximation to Hidden Markov Model Learning

open access: yesPLoS Comput. Biol., 2014
In order to cross a street without being run over, we need to be able to extract very fast hidden causes of dynamically changing multi-modal sensory stimuli, and to predict their future evolution.
D. Kappel, Bernhard Nessler, W. Maass
semanticscholar   +1 more source

Robustness and sample complexity of model-based MARL for general-sum Markov games [PDF]

open access: yesarXiv, 2021
Multi-agent reinforcement learning (MARL) is often modeled using the framework of Markov games (also called stochastic games or dynamic games). Most of the existing literature on MARL concentrates on zero-sum Markov games but is not applicable to general-sum Markov games. It is known that the best-response dynamics in general-sum Markov games are not a
arxiv  

Optimizing Metamaterial Inverse Design with 3D Conditional Diffusion Model and Data Augmentation

open access: yesAdvanced Materials Technologies, EarlyView.
A generative AI model, the 3D conditional diffusion model (3D‐CDM), is introduced to enhance the inverse design of voxel‐based metamaterials. A data augmentation technique based on topological perturbation expands the dataset, further improving generation quality and accuracy.
Xiaoyang Zheng   +2 more
wiley   +1 more source

Bayesian Parameterization of Continuum Battery Models from Featurized Electrochemical Measurements Considering Noise**

open access: yesBatteries &Supercaps, Volume 6, Issue 1, January 2023., 2023
We introduce a computer algorithm that incorporates the experience of battery researchers to extract information from experimental data reproducibly. This enables the fitting of complex models that take up to a few minutes to simulate. For validation, we process full‐cell GITT measurements to characterize the diffusivities of both electrodes non ...
Yannick Kuhn   +3 more
wiley   +1 more source

MODEL MARKOV TERSEMBUNYI

open access: yesStatistika, 2014
Model Markov Tersembunyi (Hidden Markov Model/HMM) adalah suatu pemodelan rantai Markov keadaan hingga. Setiap keadaan membangun pengamatan dan disumsikan ada barisan keadaan yang tidak dapat diamati.
Rini Marwati
doaj  

Cost-Effectiveness Analysis of Maintenance Olaparib in Patients with Metastatic Pancreatic Cancer and a Germline BRCA1/2 Mutation Based on the POLO Trial

open access: yesCancer Management and Research, 2020
Mei Zhan,1– 3 Hanrui Zheng,1– 3 Yu Yang,2,4 Zhiyao He,1 Ting Xu,1,3 Qiu Li2,4 1Department of Pharmacy, West China Hospital, Sichuan University, Chengdu, People’s Republic of China; 2West China Biomedical Big Data Center, Sichuan ...
Zhan M   +5 more
doaj  

Asymmetric hidden Markov models [PDF]

open access: yesInternational Journal of Approximate Reasoning, 2017
Abstract In many problems involving multivariate time series, hidden Markov models (HMMs) are often employed for modeling complex behavior over time. HMMs can, however, require large number of states, what can lead to poor problem insight and model overfitting, especially when limited data is available.
Marcos L. P. Bueno   +5 more
openaire   +4 more sources

Chemical AI in the Limelight: The Contribution of Photochromic Materials and Oscillatory Chemical Reactions

open access: yesAdvanced Optical Materials, EarlyView.
Photochromic compounds are versatile ingredients for the development of Chemical AI. When they are embedded in a tight microenvironment, they become Markov blankets. They are also valuable for processing Boolean and Fuzzy logic. They contribute to neuromorphic engineering in wetware based on opto‐chemical signals exchanged with oscillatory chemical ...
Pier Luigi Gentili
wiley   +1 more source

Goodness‐of‐fit tests in proportional hazards models with random effects

open access: yesBiometrical Journal, Volume 65, Issue 1, January 2023., 2023
Abstract This paper deals with testing the functional form of the covariate effects in a Cox proportional hazards model with random effects. We assume that the responses are clustered and incomplete due to right censoring. The estimation of the model under the null (parametric covariate effect) and the alternative (nonparametric effect) is performed ...
Wenceslao González‐Manteiga   +2 more
wiley   +1 more source

Information-Theoretic Reduction of Markov Chains [PDF]

open access: yesarXiv, 2022
We survey information-theoretic approaches to the reduction of Markov chains. Our survey is structured in two parts: The first part considers Markov chain coarse graining, which focuses on projecting the Markov chain to a process on a smaller state space that is informative}about certain quantities of interest.
arxiv  

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