AIMC Topic: Likelihood Functions

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Incorporating sparse labels into hidden Markov models using weighted likelihoods improves accuracy and interpretability in biologging studies.

PloS one Jun 18, 2025
Ecologists often use a hidden Markov model to decode a latent process, such as a sequence of an animal's behaviours, from an observed biologging time series. Modern technological devices such as video recorders and drones now allow researchers to dir...
Animals Likelihood Functions Whale, Killer Hidden Markov Models Markov Chains Feeding Behavior
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Ethical and security challenges in AI for forensic genetics: From bias to adversarial attacks.

Forensic science international. Genetics Jan 27, 2025
Forensic scientists play a crucial role in assigning probabilities to evidence based on competing hypotheses, which is fundamental in legal contexts where propositions are presented usually by prosecution and defense. The likelihood ratio (LR) is a w...
Forensic Genetics Pedigree Likelihood Functions Humans Artificial Intelligence Machine Learning Bias
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Machine learning in causal inference for epidemiology.

European journal of epidemiology Nov 13, 2024
In causal inference, parametric models are usually employed to address causal questions estimating the effect of interest. However, parametric models rely on the correct model specification assumption that, if not met, leads to biased effect estimate...
Humans Machine Learning Causality Epidemiologic Methods Epidemiology Models, Statistical Likelihood Functions
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Machine learning can be as good as maximum likelihood when reconstructing phylogenetic trees and determining the best evolutionary model on four taxon alignments.

Molecular phylogenetics and evolution Aug 30, 2024
Phylogenetic tree reconstruction with molecular data is important in many fields of life science research. The gold standard in this discipline is the phylogenetic tree reconstruction based on the Maximum Likelihood method. In this study, we present ...
Neural Networks, Computer Likelihood Functions Sequence Alignment Models, Genetic Evolution, Molecular Machine Learning Phylogeny
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Non-Intrusive System for Honeybee Recognition Based on Audio Signals and Maximum Likelihood Classification by Autoencoder.

Sensors (Basel, Switzerland) Aug 21, 2024
Artificial intelligence and Internet of Things are playing an increasingly important role in monitoring beehives. In this paper, we propose a method for automatic recognition of honeybee type by analyzing the sound generated by worker bees and drone ...
Artificial Intelligence Neural Networks, Computer Algorithms Bees Animals Likelihood Functions Signal Processing, Computer-Assisted
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Reliable estimation of tree branch lengths using deep neural networks.

PLoS computational biology Aug 5, 2024
A phylogenetic tree represents hypothesized evolutionary history for a set of taxa. Besides the branching patterns (i.e., tree topology), phylogenies contain information about the evolutionary distances (i.e. branch lengths) between all taxa in the t...
Models, Genetic Evolution, Molecular Deep Learning Computational Biology Likelihood Functions Sequence Alignment Neural Networks, Computer Machine Learning Algorithms Phylogeny
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Boosting integral-based human pose estimation through implicit heatmap learning.

Neural networks : the official journal of the International Neural Network Society Jul 10, 2024
Human pose estimation typically encompasses three categories: heatmap-, regression-, and integral-based methods. While integral-based methods possess advantages such as end-to-end learning, full-convolution learning, and being free from quantization ...
Algorithms Posture Likelihood Functions Neural Networks, Computer Machine Learning Humans
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Artificial neural networks for model identification and parameter estimation in computational cognitive models.

PLoS computational biology May 15, 2024
Computational cognitive models have been used extensively to formalize cognitive processes. Model parameters offer a simple way to quantify individual differences in how humans process information. Similarly, model comparison allows researchers to id...
Likelihood Functions Neural Networks, Computer Algorithms Humans Cognition Computer Simulation Models, Neurological Computational Biology
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Consideration on the learning efficiency of multiple-layered neural networks with linear units.

Neural networks : the official journal of the International Neural Network Society Jan 17, 2024
In the last two decades, remarkable progress has been done in singular learning machine theories on the basis of algebraic geometry. These theories reveal that we need to find resolution maps of singularities for analyzing asymptotic behavior of stat...
Neural Networks, Computer Likelihood Functions Generalization, Psychological
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A new method for clustered survival data: Estimation of treatment effect heterogeneity and variable selection.

Biometrical journal. Biometrische Zeitschrift Dec 10, 2023
We recently developed a new method random-intercept accelerated failure time model with Bayesian additive regression trees (riAFT-BART) to draw causal inferences about population treatment effect on patient survival from clustered and censored surviv...
Likelihood Functions Treatment Effect Heterogeneity Computer Simulation Bayes Theorem Humans Machine Learning
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