Results 21 to 30 of about 114,968,292 (129)

Miners' Reward Elasticity and Stability of Competing Proof‐of‐Work Cryptocurrencies

International Economic Review, Volume 67, Issue 3, Page 957-976, August 2026.
ABSTRACT Proof‐of‐Work cryptocurrencies employ miners to sustain the system through algorithmic reward adjustments. We develop a stochastic model of the multicurrency mining and identify conditions for stable transaction speeds. Bitcoin's algorithm requires hash supply elasticity <$<$1 for stability, while ASERT remains stable for any elasticity and ...
Kohei Kawaguchi, Junpei Komiyama, Shunya Noda   +2 more
wiley   +1 more source

Advancing Marine Bioacoustics With Deep Generative Models: A Hybrid Augmentation Strategy for Southern Resident Killer Whale Detection

Marine Mammal Science, Volume 42, Issue 3, July 2026.
ABSTRACT Automated detection and classification of marine mammal vocalizations is critical for conservation and management efforts but is hindered by limited annotated datasets and the acoustic complexity of real‐world marine environments. Data augmentation has proven to be an effective strategy to address this limitation by increasing dataset ...
Bruno Padovese, Fabio Frazao, Michael Dowd, Ruth Joy   +3 more
wiley   +1 more source

Distribution‐Guided Ensemble Postprocessing for S2S Precipitation Forecasts: A Seamless Pathway Using Deep Generative Models

Journal of Geophysical Research: Machine Learning and Computation, Volume 3, Issue 3, June 2026.
Abstract Atmosphere‐ocean‐land coupled forecasting systems, despite their comprehensiveness, face substantial challenges in the “predictability desert” at subseasonal to seasonal (S2S) timescales, particularly for precipitation—a variable crucial for socioeconomic activities yet of stunning spatiotemporal variance. Post‐processing methods developed for
Wen Shi, Baoxiang Pan, Jianbin Huang, Tingfeng Dou, Jie Feng, Huihui Yuan, Anran Wang, Xin Xia, Lei Huang, Yong Luo   +9 more
wiley   +1 more source

A review of portfolio planning: Models and systems [PDF]

, 2003
In this chapter, we first provide an overview of a number of portfolio planning models which have been proposed and investigated over the last forty years.
Mitra, G, Kyriakis, T, Lucas, CA, Pirbhai, M   +3 more
core   +4 more sources

Bayesian Decision Thresholds for Bushfire Warnings: Calibration and Robustness for Rare‐Event Risk

Australian &New Zealand Journal of Statistics, Volume 68, Issue 2, June 2026.
ABSTRACT Current bushfire warning systems communicate the probability of a warning given danger, but residents require the probability of danger given a warning. This misalignment, combined with the extreme rarity of catastrophic fires, often leads to the dangerous ‘wait and see’ behaviour.
Miodrag Lovric, Ojas Davé
wiley   +1 more source

Financial Time Series Uncertainty: A Review of Probabilistic AI Applications

Journal of Economic Surveys, Volume 40, Issue 2, Page 915-953, April 2026.
ABSTRACT Probabilistic machine learning models offer a distinct advantage over traditional deterministic approaches by quantifying both epistemic uncertainty (stemming from limited data or model knowledge) and aleatoric uncertainty (due to inherent randomness in the data), along with full distributional forecasts.
Sivert Eggen, Tord Johan Espe, Kristoffer Grude, Morten Risstad, Rickard Sandberg   +4 more
wiley   +1 more source

Generative Models for Crystalline Materials

Advanced Materials, Volume 38, Issue 18, 25 March 2026.
Generative machine learning models are increasingly used in crystalline materials design. This review outlines major generative approaches and assesses their strengths and limitations. It also examines how generative models can be adapted to practical applications, discusses key experimental considerations for evaluating generated structures, and ...
Houssam Metni, Laura Ruple, Lauren N. Walters, Luca Torresi, Jonas Teufel, Henrik Schopmans, Jona Östreicher, Yumeng Zhang, Marlen Neubert, Yuri Koide, Kevin Steiner, Paul Link, Lukas Bär, Mariana Petrova, Gerbrand Ceder, Pascal Friederich   +15 more
wiley   +1 more source

Diffusion‐MRI‐Based Estimation of Cortical Architecture via Machine Learning (DECAM) in Primate Brains

Advanced Science, Volume 13, Issue 14, 9 March 2026.
We present Diffusion‐MRI‐based Estimation of Cortical Architecture via Machine Learning (DECAM), a deep‐learning framework for estimating primate brain cortical architecture optimized with best response constraint and cortical label vectors. Trained using macaque brain high‐resolution multi‐shell dMRI and histology data, DECAM generates high‐fidelity ...
Tianjia Zhu, Minhui Ouyang, Shufang Tan, Jianlin Guo, Ziqin Zhang, Xuan Liu, Risheng Liu, Hao Huang   +7 more
wiley   +1 more source

Recanting Twins: Addressing Intermediate Confounding in Mediation Analysis

Statistics in Medicine, Volume 45, Issue 3-5, February 2026.
ABSTRACT The presence of intermediate confounders, also called recanting witnesses, is a fundamental challenge to the investigation of causal mechanisms in mediation analysis, preventing the identification of natural path‐specific effects. Common alternatives (such as randomizational interventional effects) are problematic because they can take non ...
Tat‐Thang Vo, Nicholas Williams, Richard Liu, Kara E. Rudolph, Iván Díaz   +4 more
wiley   +1 more source

Transition‐Aware Q‐Learning for Robust Tracking in Networked Control Systems with Fading Channels: Application to Leader−Follower Vehicle Control

IET Control Theory &Applications, Volume 20, Issue 1, January/December 2026.
Maintaining reliable tracking control in networked control systems over fading wireless channels is difficult due to the stochastic and time‐correlated nature of wireless links. This work proposes a transition‐aware Q‐learning (TA‐QL) method that learns robust control policies directly from networked data without requiring explicit models, while ...
Ehsan Badfar, Babak Tavassoli
wiley   +1 more source