Results 131 to 140 of about 241,122 (289)

A Temporally Disentangled Contrastive Diffusion Model for Spatiotemporal Imputation

CAAI Transactions on Intelligence Technology, EarlyView.
ABSTRACT The analysis of spatiotemporal data is essential across many fields, such as transportation, meteorology and healthcare. Data gathered in practical applications often suffer from incompleteness due to device failures and network disruptions.
Yakun Chen, Kaize Shi, Zhangkai Wu, Juan Chen, Xianzhi Wang, Julian McAuley, Guandong Xu, Shui Yu   +7 more
wiley   +1 more source

Temporal Dependency‐Aware Trajectory‐Level Behavioural Metric for Exploration in Reinforcement Learning

CAAI Transactions on Intelligence Technology, EarlyView.
ABSTRACT Intrinsic motivation serves as the predominant paradigm of exploration in reinforcement learning. In pursuit of an informative and robust state representation, the behavioural metric groups behaviourally equivalent states together, which share the same single‐step reward and transition distribution.
Anjie Zhu, Yongjun Yang, Guangyi Zhao, Jie Shao   +3 more
wiley   +1 more source

Time-delay estimation for compound point-processes using hidden Markov models

, 2002
Jens Wohlers, Alfred Mertins, N.J. Fliege   +2 more
openalex   +1 more source

Penerapan Hidden Markov Model (HMM) dan Mel-Frequency Cesptral Coefficients (MFCC) pada E-Learning Bahasa Madura untuk Anak Usia Dini [PDF]

, 2020
Ubaidi Ubaidi, Nindian Puspa Dewi
openalex   +1 more source

Towards Generalisable and Explainable Traffic Signal Control via Deep Reinforcement Learning and Large Language Models

CAAI Transactions on Intelligence Technology, EarlyView.
ABSTRACT As a government‐regulated public service, traffic signal control (TSC) requires reliable and transparent decision‐making. However, existing deep reinforcement learning (DRL) methods, despite improvements in control accuracy, still lack explainability and generalisation, severely limiting their applicability in real‐world environments.
Hao Huang, Wenjie He, Qilie Liu, Qian Liu, Chao Huang, Anwar P. P. Abdul Majeed, Xiangguang Dai, Gang Fang, Xiaohua Xu   +8 more
wiley   +1 more source

Improving on hidden Markov models: An articulatorily constrained, maximum likelihood approach to speech recognition and speech coding

, 1996
John Hogden
openalex   +2 more sources

Multi‐Agent Reinforcement Learning Driven Dynamic Resource Optimisation in Healthcare Transportation Networks

CAAI Transactions on Intelligence Technology, EarlyView.
ABSTRACT This paper presents HealthNet, a novel framework for the dynamic optimisation of healthcare transportation networks using multi‐agent reinforcement learning. HealthNet leverages a spatiotemporal dependency module to capture complex spatiotemporal relationships in healthcare demand and resource allocation patterns, combined with centralised ...
Jianhui Lv, Byung‐Gyu Kim, Keqin Li, Heng Lu   +3 more
wiley   +1 more source

Cost‐Optimal Building Energy System Scheduling Integrating Solar Irradiance Forecasting via LSTM‐Attention‐TCN Model

CAAI Transactions on Intelligence Technology, EarlyView.
ABSTRACT Building energy systems integrating multiple energy sources can effectively reduce energy consumption and facilitate renewable energy integration. Integrating electrical energy storage (EES) into these systems helps accommodate the increasing share of renewables; however, the stochastic and intermittent nature of solar power still poses ...
Zhengtian Wu, Jianyu Li, Yang Gao, Chuangyin Dang, Chao Tang, Yuansheng Li, Xinmiao Wang, Jinpeng Chen, Hongbo Gao, Xinyin Xu   +9 more
wiley   +1 more source

An exemplar-based hidden Markov model framework for nonlinear state-space models

, 2016
Redouane Lguensat, Ronan Fablet, Pierre Ailliot, Pierre Tandeo   +3 more
openalex   +2 more sources

Learning Dependencies of Discrete Speech Representations with Neural Hidden Markov Models [PDF]

, 2022
Sung-Lin Yeh, Hao Tang
openalex   +1 more source