Results 61 to 70 of about 19,768 (155)
ABSTRACT Genomic selection (GS) is critical for accelerating genetic gain in modern plant breeding. Deep learning approaches offer powerful non‐linear representation capabilities for modelling non‐additive effects. However, their application in GS remains restricted, as high‐dimensional, low‐sample and noisy data hinder the identification of ...
Yuexin Ma +7 more
wiley +1 more source
About Adaptive Coding on Countable Alphabets: Max-Stable Envelope Classes
In this paper, we study the problem of lossless universal source coding for stationary memoryless sources on countably infinite alphabets. This task is generally not achievable without restricting the class of sources over which universality is desired ...
Gassiat, Elisabeth +2 more
core +1 more source
The novel family of redundant residue number system (RRNS) codes is studied. RRNS codes constitute maximum–minimum distance block codes, exhibiting identical distance properties to Reed–Solomon codes.
Hanzo, L., Liew, T.H., Yang, L-L.
core +1 more source
Re‐Imagining Regulatory Governance
ABSTRACT This paper invites the readers to rethink regulatory governance by examining how trust‐based and rule‐based governance interact. To do this, it uses analytical narratives of three fictional polities: “Trustland”, “Regland”, and “Concordia”. Each polity represents a stylized model of governance: Trustland is anchored in trust‐based governance ...
David Levi‐Faur
wiley +1 more source
Practical Full Resolution Learned Lossless Image Compression
We propose the first practical learned lossless image compression system, L3C, and show that it outperforms the popular engineered codecs, PNG, WebP and JPEG 2000.
Agustsson, Eirikur +4 more
core +1 more source
Causal Effect Estimation With TMLE: Handling Missing Data and Near Violations of Positivity
ABSTRACT We evaluate the performance of targeted maximum likelihood estimation (TMLE) for estimating the average treatment effect in missing data scenarios under varying levels of positivity violations. We employ model‐ and design‐based simulations, with the latter using undersmoothed highly adaptive lasso on the “WASH Benefits Bangladesh” data set to ...
Christoph Wiederkehr +2 more
wiley +1 more source
Abstract Diagnostic classification models (DCMs) assess students’ mastery of cognitive attributes to provide personalized ability profiles. Retrofitting DCMs to large‐scale mathematics assessments usually relies on inferred Q‐matrices, which can reduce accuracy and diagnostic value.
Farshad Effatpanah +4 more
wiley +1 more source
Fairness at Risk: Where Bias Emerges in Machine Learning
ABSTRACT Artificial intelligence and machine learning (ML) now shape decisions in healthcare, finance and security, but they can reproduce historical prejudice and inequality. Bias in training data and in model implementation can amplify harm, especially for racial and gender minorities.
Otavio de Paula Albuquerque +2 more
wiley +1 more source
Accelerating Catalyst Materials Discovery With Large Artificial Intelligence Models
AI‐empowered catalysis research via integrated database platform, universal machine learning interatomic potentials (MLIPs), and large language models (LLMs). ABSTRACT The integration of artificial intelligence (AI) into catalysis is fundamentally reshaping the research paradigm of catalyst discovery.
Di Zhang +7 more
wiley +2 more sources
Perceptual Copyright Protection Using Multiresolution Wavelet-Based Watermarking And Fuzzy Logic
In this paper, an efficiently DWT-based watermarking technique is proposed to embed signatures in images to attest the owner identification and discourage the unauthorized copying.
Hsieh, Ming-Shing
core +3 more sources

