Bayesian CNN estimates uncertainty in bone age prediction.
problem Uncertainty quantification in age estimation models.
method Variational Inference for Bayesian CNNs.
result Model uncertainty distinguished from data uncertainty.
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48 results for “age inference”
Bayesian method infers ages of 700M Twitter users from follow data.
problem Lack of demographic data on Twitter users.
method Bayesian framework to generalize age information from a few users to the entire network.
result Highly accurate age inference for 700 million Twitter accounts.
Novel U-learning method for predicting continuous outcomes from high-dimensional data.
problem Challenges in making valid inferences on predictions from high-dimensional inputs.
method U-learning via combinatory multi-subsampling for ensemble predictions and confidence intervals.
result Valid inferences on predictions from Lasso and neural networks.
BIGMACS aligns multiple ocean sediment cores using Bayesian inference and Gaussian process regression.
problem Aligning and synchronizing ages from different ocean sediment cores using multiple proxies.
method BIGMACS uses Bayesian inference and Gaussian process regression to align and integrate age proxies.
result Constructs a new Deep Northeastern Atlantic stack and age models for additional cores.
AG-RL uses action grammars to improve reinforcement learning efficiency.
problem Improving sample efficiency in reinforcement learning.
method Integrates action grammars into reinforcement learning algorithms to enhance performance.
result Significant improvement in performance across multiple Atari games.
The paper uses AI to analyze ECG data, revealing age-related changes and identifying key features.
problem Investigating age-related changes in ECG data to distinguish healthy from disease-related changes.
method Employed deep-learning and tree-based models on raw ECG signals and features from a diverse age group.
result Identified age-related declines in breathing rates and high SDANN values in elderly individuals.
Model learns aging rates from single cross-sectional data.
problem Cross-sectional data limits traditional time-series methods.
method Latent-variable model with order-isomorphic nonlinear function.
result Reconstructs aging rates from single cross-sectional data.
Predicts user age and gender on Tumblr using rich content.
problem Challenges in targeting specific demographic groups on Tumblr.
method Graph based and deep learning models, including network embedding, label propagation, CNN, and MLP.
result Significantly improved accuracy for age and gender predictions.
Unified VAE for brain aging analysis improves regression accuracy.
problem Applying VAE to supervised learning for brain imaging data.
method Unified probabilistic model for latent space learning with conditional distribution modeling.
result Model predicts age from MR images more accurately than state-of-the-art methods.
VNNs transfer well across datasets for brain age prediction using cortical thickness features.
problem Predicting brain age using anatomical features.
method Transferability of coVariance neural networks (VNNs) in brain age prediction.
result VNNs can assign anatomical interpretability to elevated brain age gap in AD.
Adversarial framework enforces fairness constraints on graph embeddings.
problem Fairness constraints in graph embeddings, especially age and gender.
method Adversarial framework for compositional fairness constraints.
result Framework allows for flexible combinations of fairness constraints.
Method converts age labels into distributions to improve speaker age estimation.
problem Label ambiguity in age labels makes precise speaker age estimation challenging.
method Converts age labels into label distributions and uses label distribution learning.
result Our method outperforms baseline methods by reducing MAE by 10% on a real-world dataset.
Bayesian approach predicts brain-age from EEG sleep states across age.
problem Inconsistent brain-age predictions due to subjective sleep state classification.
method Unified Bayesian Network with Gaussian Mixture Models for EEG sleep states.
result Improved accuracy in brain-age prediction over a wider age range.
The paper models retirement spending using biological age instead of chronological age.
problem Retirement spending varies at the same chronological age.
method Developed a stochastic mortality model to adjust for biological age.
result Optimal consumption rates derived using biological age.
Unified model for age-invariant face recognition with photorealistic face synthesis.
problem Reliable face recognition across ages remains challenging due to significant intra-class variations.
method Unified deep architecture for cross-age face synthesis and recognition, continuous face rejuvenation/aging, disentangled age-invariant face representations.
result Superior performance on CAFR and other cross-age datasets, promising generalizability to unconstrained face recognition.
SFCNeXt estimates brain age from small MRI datasets.
problem Efficiently estimating brain age from limited MRI data.
method Simple fully convolutional network (SFCNeXt) with SPEC and HRL.
result SFCNeXt outperforms complex models in small sample size scenarios.
Deep learning predicts brain age from raw MRI data with high accuracy and reliability.
problem Predicting brain age from neuroimaging data to assess individual differences in brain aging.
method Convolutional Neural Networks (CNN) applied to raw T1-weighted MRI data.
result Brain-predicted age is a reliable and heritable biomarker of brain aging.
New method uses AI predictions as cheaper alternatives to expensive outcomes.
problem Using expensive outcomes for statistical inference.
method Recalibrated prediction-powered inference using machine learning techniques.
result Significant gains in effective sample size over existing PPI proposals.
Study uses deep learning with attention to predict fetal brain gestational age.
problem Accurately predicting fetal brain gestational age for early diagnosis.
method Attention-based deep learning model combining multi-view MRI data.
result Age prediction performance with R2 = 0.94 using multi-view MRI and attention.
Improved sex and age-specific model for Parkinson's diagnosis.
problem Accurate diagnosis of Parkinson's disease for better patient care.
method Sex-specific and age-dependent handwriting classification model.
result Significantly improved accuracy (83.75% for females, 79.55% for older age group) compared to generalized model.
Paper tackles deconfounding age effects in dementia detection models.
problem Dementia detection models are affected by age, leading to potential non-generalizable accuracies.
method Proposes fair representation learning to learn age-invariant representations.
result Best models compromise accuracy by only 2.56% and 1.54% on clinical datasets.
3D CNN accurately classifies infant neurodevelopmental age from MRI scans.
problem Estimating neurodevelopmental age in infants from MRI data.
method 3D Convolutional Neural Network (3D CNN) trained on MRI images of 112 infants.
result 3D CNN achieves 99% sensitivity and 98.3% specificity in age classification.
Develops a method to analyze SARS-CoV-2 viral load vs. age, finding a significant increase.
problem Determining if SARS-CoV-2 viral load depends on patient age.
method Flexible, non-parametric, hierarchical, Bayesian, causal model.
result Statistically significant increase in viral load with age, but only for one dataset.
Optimizes consumption, investment, and healthcare spending for aging populations.
problem Maximizing utility in an aging population with changing mortality rates.
method Solves an optimal stochastic control problem using a novel version of Perron's method.
result Endogenous mortality law that is asymptotically exponential in the old-age limit.
Estimates future ICU demand using age-structured data and logistic modeling.
problem Projecting future ICU demand from low-quality data.
method Age-structured sampling, logistic fit, subnotification factor correction.
result Corrected logistic curve projects future ICU demand.
Predicts gender and age from mobile phone data for marketing.
problem Enhance marketing offers by predicting customer demographics.
method Machine learning algorithms applied to CDRs, CRM, and billing info.
result 85.6% accuracy in gender prediction, 65.5% in age prediction.
Probabilistic programming aids in automatically dating ice cores, reducing manual error and uncertainty.
problem Automatically dating ice cores with high accuracy and capturing uncertainty.
method Probabilistic models and probabilistic programming for automatic inference.
result Demonstrated the use of probabilistic programming for ice core dating, showcasing its benefits and limitations.
Italy's daily COVID-19 cases stratified by age groups.
problem Analyzing the spread and impact of COVID-19 across different age groups.
method Stratified daily data of COVID-19 cases by age classes.
result Detailed insights into how age affects COVID-19 outcomes.
A new FL algorithm reduces communication overhead by selectively updating model parameters.
problem Data heterogeneity and communication overhead in federated learning.
method Uses age of information metric to selectively update model parameters and group clients with similar data.
result Our method can expedite training and surpass other communication-efficient strategies in efficiency.
AGE improves graph embedding by smoothing features and iteratively enhancing node embeddings.
problem Challenges in attributed graph embedding, especially in preserving optimal low-pass characteristics and robustness.
method AGE, a novel framework combining Laplacian smoothing and adaptive encoding, addresses these issues.
result AGE consistently outperforms state-of-the-art methods on node clustering and link prediction tasks.
Study reveals that cryptocurrency price variations follow power-law distributions, influenced by age and market capitalization.
problem Understanding the statistical properties of cryptocurrencies, especially their price variations.
method Comprehensive investigation of over 7000 digital currencies, analyzing their price returns over time.
result Cryptocurrency price returns follow power-law distributions, with age and market capitalization influencing these distributions.
The modal age of Statisticsstat.ME
Modern statistical methods find the most common value in data.
problem Finding the most common value in data.
method Modern statistical methods applied to mode estimation.
result Traditional approaches to mode estimation are explored and modern methods are applied to new fields.
NEON+: Accelerated Gradient Methods for Extracting Negative Curvature for Non-Convex Optimizationmath.OC
This paper accelerates gradient methods to find local minima in non-convex optimization.
problem Finding local minima in non-convex optimization problems.
method Polyak's Heavy Ball method and Nesterov's Accelerated Gradient method for extracting negative curvature.
result A new AG algorithm converges to second-order stationary points with improved iteration complexity.
Combining Unsupervised and Supervised Learning for Asset Class Failure Prediction in Power Systemsstat.AP
Paper proposes a new approach to predict power system asset class failures.
problem Predicting failures for different asset classes in power systems is critical for cost-effective asset management.
method Combines unsupervised (K-means clustering) and supervised (logistic regression) learning methods using asset condition data.
result The proposed approach outperforms standard methods in predicting asset class failures.
Machine learning models predict brain age with systematic bias, corrected in this study.
problem Systematic bias in machine learning regression models for brain age prediction.
method General constrained optimization approach to correct bias.
result Our method effectively eliminates the bias from brain age predictions.
Modeling retirement behavior with public pension, optimal consumption and housing decisions.
problem Retirement behavior, consumption, housing, investment, and public pension effects.
method Expected utility model, stochastic control problem, maximum likelihood method.
result Optimal housing, consumption, and risky asset allocation depend on age and wealth, sensitive to means-tested Age Pension.
Proposes a new model for mortality forecasting considering age groups and cohort effects.
problem Longevity risk due to ageing population.
method Mixed-effects time-series approach with age groups dependency and random cohort effects.
result Remarkable improvements in forecast accuracy compared to the CBD model.
Optimal annuitization strategy depends on age, labor income, and mortality risk.
problem Maximizing utility from consumption and labor income under age-dependent mortality.
method Dynamic programming approach to derive closed-form solutions.
result Post-retirement labor income acts as a substitute for annuitization.
Deep CNNs identify age-related patterns in fetal brain activity.
problem Understanding age effects in fetal brain development.
method Supervised 3D Convolutional Neural Networks applied to fetal fMRI data.
result Deep CNNs can distinguish age groups in fetal brain activity.
4-dim intrinsic (material) Riemannian metric of the material 4-D space-time continuum is utilized as the characteristic of the aging processes developing in the material. Manifested through variation of basic material characteristics such as density, moduli of elasticity, yield stress, strength, and toughness.,…
The paper uses distance correlation for brain connectivity and a novel multi-task learning model for age prediction.
problem Estimating age-related gender differences in brain functional connectivity.
method Estimates functional connectivity using distance correlation and proposes a non-convex multi-task learning model.
result The proposed non-convex multi-task learning model outperforms other models in age prediction and gender-specific connectivity.
In order to investigate the breast cancer prediction problem on the aging population with the grades of DCIS, we conduct a tree augmented naive Bayesian network experiment trained and tested on a large clinical dataset including consecutive diagnostic mammography examinations, consequent biopsy outcomes and related can…
We derive a cut-and-paste surgery formula of Seiberg--Witten invariants for negative definite plumbed rational homology 3-spheres. It is similar to (and motivated by) Okuma's recursion formula [arXiv:math.AG/0610464, 4.5] targeting analytic invariants of splice quotient singularities. The two formulas combined provide …
Paper harmonizes medical data using flow-based causal inference.
problem Heterogeneity in medical data from different sites and protocols.
method Flow-based normalizing method for counterfactual inference on structural causal models.
result Better cross-domain generalization compared to state-of-the-art algorithms.
Adaptive model improves age prediction from DNA methylation data.
problem Improving age prediction from DNA methylation data with heterogeneity.
method Adaptive model for feature selection based on individual sample distributions.
result Substantial improvement in age prediction for one tissue type.
Changes in Australian Age Pension mean-tests affect retirement planning and benefits.
problem Policy changes impact optimal retirement decisions and benefits.
method Optimal stochastic control problem in a utility maximizing lifecycle model.
result New rules decrease benefits from means-testing but increase housing allocation slightly.
Predicts the age of astronomical transients from real-time data.
problem Improving understanding of transients and their progenitor systems.
method Bayesian probabilistic recurrent neural network.
result Accurately predicts the age of transients with robust uncertainties.
Develops a GP framework for age and year-specific mortality surfaces.
problem Learning the covariance structure of age and year-specific mortality surfaces.
method Genetic programming algorithm to search for the most expressive GP kernel.
result Reveals the presence/absence of cohort effects in different populations.