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
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]
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
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
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 (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
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]
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
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
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]
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