Results 11 to 20 of about 123,697 (193)
Locally Adaptive Dynamic Networks
, 2016 Our focus is on realistically modeling and forecasting dynamic networks of face-to-face contacts among individuals. Important aspects of such data that lead to problems with current methods include the tendency of the contacts to move between periods of ...
Dunson, David B., Durante, Daniele
core +1 more source
The Block Point Process Model for Continuous-Time Event-Based Dynamic Networks
, 2019 We consider the problem of analyzing timestamped relational events between a set of entities, such as messages between users of an on-line social network.
Devabhaktuni, Vijay K. +3 more
core +1 more source
Applied Computer ScienceStationarity is a fundamental assumption in time series modeling that underlies reliable statistical inference and forecasting. Time series data can be found in many domains, including industry, engineering, finance, economics, epidemiology, and health ...
Apollinaire BATOURE BAMANA +3 more
doaj +1 more source
Resolving the structure of interactomes with hierarchical agglomerative clustering
BMC Bioinformatics, 2011 Background Graphs provide a natural framework for visualizing and analyzing networks of many types, including biological networks. Network clustering is a valuable approach for summarizing the structure in large networks, for predicting unobserved ...
Park Yongjin, Bader Joel S
doaj +1 more source
What Do Large Language Models Know About Materials?
Advanced Engineering Materials, EarlyView.If large language models (LLMs) are to be used inside the material discovery and engineering process, they must be benchmarked for the accurateness of intrinsic material knowledge. The current work introduces 1) a reasoning process through the processing–structure–property–performance chain and 2) a tool for benchmarking knowledge of LLMs concerning ...
Adrian Ehrenhofer +2 more
wiley +1 more source
Hybrid machine learning algorithms accurately predict marine ecological communities
Frontiers in Marine SciencePredicting ecological communities is highly challenging but necessary to establish effective conservation and monitoring programs. This study aims to predict the spatial distribution of nematode associations from 25 m to 2500 m water depth over an area ...
Luciana Erika Yaginuma +7 more
doaj +1 more source
Understanding and Comparing Scalable Gaussian Process Regression for Big Data
, 2018 As a non-parametric Bayesian model which produces informative predictive distribution, Gaussian process (GP) has been widely used in various fields, like regression, classification and optimization.
Cai, Jianfei +3 more
core +1 more source
Advanced Functional Materials, EarlyView.An all‐in‐one analog AI accelerator is presented, enabling on‐chip training, weight retention, and long‐term inference acceleration. It leverages a BEOL‐integrated CMO/HfOx ReRAM array with low‐voltage operation (<1.5 V), multi‐bit capability over 32 states, low programming noise (10 nS), and near‐ideal weight transfer.
Donato Francesco Falcone +11 more
wiley +1 more source
Amortized Parameter Inference for the Arbitrary-Order Hidden Markov Model
AxiomsThe arbitrary-order hidden Markov model (α-HMM) is a nontrivial generalization of the standard HMM, designed to model stochastic processes with higher-order dependences among arbitrarily distant random events.
Sixiang Zhang, Liming Cai
doaj +1 more source
Advanced Functional Materials, EarlyView.A large number of MoS2 flakes were screened to obtain high‐quality flakes based on optical intensities in R, G, and B channel images. The flakes were classified from Level 1 to 6 based on optical intensities in the R, G, and B channel images. Low‐quality flake exhibited wrinkled, folded, or overlapped features, while high‐quality displayed a neat ...
Sanghyun Lee +11 more
wiley +1 more source