Results 131 to 140 of about 136,474,496 (243)
A Wildlife Multi‐Modal Recognition Method Based on Infrared Camera Images Using MWAC
Integrative Zoology, EarlyView.A multimodal wild wildlife classification model MWAC consists of two parts:(1) Wavelet KAN module (WDS‐KAN) for image feature extraction, and (2) Label Correlated Text Extraction module (LC‐BERT) for text feature extraction. ABSTRACT Nowadays, infrared camera technology has become an important tool for large‐scale monitoring and assessment of wildlife ...
Siming Deng +6 more
wiley +1 more source
On Sequential Maximum a Posteriori Inference for Continual Learning
2025 International Joint Conference on Neural Networks (IJCNN)We formulate sequential maximum a posteriori inference as a recursion of loss functions and reduce the problem of continual learning to approximating the previous loss function. We then propose two coreset-free methods: autodiff quadratic consolidation, which uses an accurate and full quadratic approximation, and neural consolidation, which uses a ...
Menghao Waiyan William Zhu +1 more
openaire +2 more sources
Contemporary Accounting Research, EarlyView.ABSTRACT Financial accounting standard setters recently changed the accounting for estimates involving credit risk. The change shifted the accounting from an incurred‐loss model (ILM), which is based on credit‐risk conditions that exist at the time of the estimate, to a model based on expected credit losses over the life of the asset in question (ELM),
Lisa Koonce +3 more
wiley +1 more source
Maximum a posteriori vs maximum probability recursive sparse estimation
, 2015 Recursive sparse parameter estimates obtained using the author's recent maximum a posteriori (MAP) approach, where the sparse parameter estimates are determined as the a posteriori mode of a Gaussian sum filter, are compared with a new maximum ...
Blackhall, Lachlan, Rotkowitz, Michael
core
A Bayes factor framework for unified parameter estimation and hypothesis testing
British Journal of Mathematical and Statistical Psychology, EarlyView.Abstract The Bayes factor, the data‐based updating factor of the prior to posterior odds of two hypotheses, is a natural measure of statistical evidence for one hypothesis over the other. We show how Bayes factors can also be used for parameter estimation.
Samuel Pawel
wiley +1 more source
British Journal of Mathematical and Statistical Psychology, EarlyView.Abstract Although full‐information maximum likelihood (FIML) estimation is widely used for diagnostic classification models (DCMs), its computational efficiency deteriorates sharply in high‐dimensional settings. This scalability challenge is increasingly critical as DCMs are applied to large‐scale assessments, psychological testing and longitudinal ...
Minho Lee, Yon Soo Suh
wiley +1 more source
Maximum A Posteriori Least-Squares Temporal Difference
2025 American Control Conference (ACC)Least-squares Temporal Difference (LSTD) is a model-free method to estimate the cost/value function of a Markov Decision Process (MDP). Interestingly, it is equivalent to estimating the state transition probabilities of the MDP through Maximum Likelihood (ML) and computing the cost/value function with (model-based) policy evaluation. However, LSTD does
van Zuijlen, R.A.C. +1 more
openaire +3 more sources
Calibrating Bayesian inference
British Journal of Mathematical and Statistical Psychology, EarlyView.Abstract Bayesian statistics has gained popularity in psychological research due to its intuitive uncertainty quantification and convenient information‐updating rules. In many applications, however, prior distributions are introduced merely as instruments to facilitate computation, rather than as representations of genuine subjective belief ...
Yang Liu +2 more
wiley +1 more source
EURASIP Journal on Advances in Signal Processing, 2006 We present a novel hybrid scheme called "hyper-resolution" that integrates image probability-filtering-based interpolation and improved Poisson maximum a posteriori (MAP) super-resolution to respectively enhance high spatial and spatial-frequency ...
Pan Min-Cheng
doaj +1 more source
British Journal of Mathematical and Statistical Psychology, EarlyView.Abstract Cognitive diagnostic models (CDMs) have become essential tools for providing fine‐grained information about individuals' mastery of cognitive skills. While prior reviews have emphasized statistical foundations and deep learning‐based developments, this article focuses on recent methodological innovations designed to address persistent ...
Chun Wang, Yale Quan, David Arthur
wiley +1 more source