“Since the quality of data-driven ROMs is sensitive to the quality of the limited training data, we seek to identify training parameters for which using the associated training data results in the best possible parametric ROM.”

“The core algorithm chosen for the project is Multinomial Naive Bayes, primarily due to its simplicity, interpretability, and suitability for short text data.”

“What if the key to building truly intelligent machines isn't bigger models, but smarter ones?”

“B-Trans effectively leverage the wisdom of crowds, yielding superior semantic diversity while achieving better task performance compared to deterministic baselines.”

“The paper presents an online variational inference framework to compute its approximation at each time step.”

“The paper introduces the orthant normal distribution in its general form and shows how it can be used to structure prior dependence in the Bayesian elastic net regression model.”

“Despite the formal identification result, the ability to learn about monotonicity from data in practice is severely limited.”

“AODDiff inherently enables uncertainty quantification via multiple sampling, offering critical confidence metrics for downstream applications.”

“DTI-GP outperforms state-of-the-art solutions, and it allows (1) the construction of a Bayesian accuracy-confidence enrichment score, (2) rejection schemes for improved enrichment, and (3) estimation and search for top-$K$ selections and ranking with high expected utility.”

“For any objective with log-sum-exp structure over distances or energies, the gradient with respect to each distance is exactly the negative posterior responsibility of the corresponding component: $\partial L / \partial d_j = -r_j$.”

“The Bayesian analysis demonstrates that the observational bounds are effective in significantly constraining the low-density region of the equation of state.”

“gg-Mix assumes only independence between the normal means and variances, without imposing any structural restrictions on their distributions.”

“The proposed method substantially improves power when p-values are conservative, while achieving comparable performance to existing methods when p-values are exact.”

“The Bayesian DP algorithm alternates between posterior updates and value iteration, employing an estimator for the risk-based Bellman operator that combines Monte Carlo sampling with convex optimization.”

“The newly proposed mCCAdL thermostat achieves a substantial improvement in the numerical stability over the original CCAdL thermostat, while significantly outperforming popular alternative stochastic gradient methods in terms of the numerical accuracy for large-scale machine learning applications.”

“The paper introduces Energy-Aware Bayesian-CBFs (EB-CBFs) that construct conservative energy-based barriers directly from the Hamiltonian and vector-field posteriors, yielding safety filters that minimally modify a nominal controller while providing probabilistic energy safety guarantees.”

“The paper proposes 'weighted geometric mean' odds ratios and relative risks, and 'weighted mean' risk differences as transparent summary measures for ordinal outcomes.”

“Any proper species sampling process can be written, at the prior level, as a finite mixture with a latent truncation variable and reweighted atoms, while preserving its distributional features exactly.”

“TRL achieves excellent calibration, matching or exceeding the reliability of Deep Ensembles (in terms of ECE) while requiring only a fraction (1/5) of the training cost.”

“The paper proposes a two-step MCMC-algorithm in a Bayesian framework to overcome the issue of partial observations.”

“The proposed method significantly outperforms state-of-the-art (SOTA) methods. Compared to SOTA methods, it improves the position accuracy by 24.7% to 42.9%, and the angular accuracy by 40.9% to 78.4%.”

“BSD consistently yields higher test accuracy (e.g. +1.4% for ResNet-50 on CIFAR-100) and significantly lower Expected Calibration Error (ECE) (-40% ResNet-50, CIFAR-100) than existing architecture-preserving self-distillation methods.”

“The paper introduces a novel methodology that integrates Bayesian Optimization (BO) to optimize the energy infrastructure together with an operating strategy optimization to reduce the electricity costs while enhancing grid interaction.”

“CVC rethinks the role of velocity in inter-distribution transformation by introducing a dual-perspective velocity conversion mechanism.”

“The paper employs Bayesian model calibration (BMC) for probabilistic estimates of material parameters and conducts global sensitivity analysis to quantify the impact of uncertainties.”

“The SPDE-based extensions improve both point and probabilistic forecasts relative to standard benchmarks.”

“The VBSF architecture achieves an accuracy of more than 98%.”

“The Bayesian joint model consistently outperforms conventional two-stage approaches in terms of parameter estimation accuracy and predictive performance.”

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“The paper proposes improvements to MCMC algorithms and compares post-processing methods to stabilize the results of Bayesian profile regression mixture models.”

“Upfront factor screening, for reducing the search space, is helpful when the goal is to find the optimal resource configuration with an affordable sampling budget. When the goal is to statistically compare different algorithms, screening must also be applied to make data collection of all data points in the search space feasible. If the goal is to find a near-optimal configuration, however, it is better to run bayesian optimization without screening.”

“The article likely details the methodology, results, and potential advantages of the proposed approach.”

“The paper develops a dynamic CKM construction method for multiple-input multiple-output orthogonal frequency division multiplexing (MIMO-OFDM) systems.”

“The authors find 'tentative evidence for a month-scale QPO; however, its detection significance is limited by the small number of observed cycles.'”

“The paper provides an elicitation method using only observable menu-choice data of the principal, which shows how to construct the principal's subjective costs of acquiring information even when he anticipates managing the agent's bias.”

“The study finds that a Binary Neutron Star (BNS) progenitor is favored for several GRBs, while for others, both BNS and Neutron Star-Black Hole (NSBH) scenarios are viable. The paper also provides insights into the KN emission parameters, such as the median wind mass.”

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“The natural log of Bayes factor for the cosine model compared to the constant value model to be less than 1.15... This shows that there is no evidence for cosine signal from dark matter interactions in the combined ANAIS-112/COSINE-100 data.”

“The paper introduces the Bayesian effective dimension, a model- and prior-dependent quantity defined through the mutual information between parameters and data.”

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“Some things really are too good to be true, like this GaN charger from eBay.”

“The paper establishes tight distribution-dependent and -independent bounds for binary classification and extends these bounds to multi-class classification, including adversarial scenarios.”

“The study derives robust limits of $E_{ m QG,1} \ge 4.37 imes 10^{16}$~GeV for linear LIV and $E_{ m QG,2} \ge 3.02 imes 10^{8}$~GeV for quadratic LIV.”

“The capability of state-of-the-art mixed logit models to reveal the true Nash equilibria seems to be primarily contingent upon the type of choice behavior (probabilistic versus deterministic).”

“FGMNB consistently outperforms five state-of-the-art embedding-based baselines on three of these networks.”

“Our framework offers an effective and theoretically grounded solution for social bot detection, significantly enhancing cybersecurity measures in social networks.”

“The paper introduces "Trustworthy Variational Bayes (TVB), a method to recalibrate the UQ of broad classes of VB procedures... Our approach follows a bend-to-mend strategy: we intentionally misspecify the likelihood to correct VB's flawed UQ.”

“The paper finds that no single model space prior consistently outperforms others across all scenarios, and the MD prior offers a valuable alternative, positioned between commonly used Beta-Binomial priors.”

“AutoQuant encodes strict T+1 execution semantics and no-look-ahead funding alignment, runs Bayesian optimization under realistic costs, and applies a two-stage double-screening protocol.”

“The core result is an 'advantage-based routing law' for attention scores and a 'responsibility-weighted update' for values, which together induce a positive feedback loop.”