Results 51 to 60 of about 12,928 (140)
Advances in Generative Models for Accelerated Discovery of New Materials
cScience, Volume 2, Issue 1, March 2026.ABSTRACT The discovery of new materials can drive tremendous social and technological progress. However, the vastness of the material space makes comprehensive exploration computationally infeasible. This paper reviews the inverse design methods of generative models in materials science, aiming to discover customized materials based on specific ...
Yuan Jiang +6 more
wiley +1 more source
Engineering Reports, Volume 8, Issue 3, March 2026.This work presents a deep learning framework for sealant inspection in automotive manufacturing, leveraging synthetic data to address the scarcity of real defects. Integrated with state‐of‐the‐art deep learning methods, the approach enhances anomaly detection and localization, demonstrating practical applicability and robustness under real‐world ...
Francesco Manigrasso +3 more
wiley +1 more source
Advances in Modal Regression: From Theoretical Foundations to Practical Implementations
WIREs Computational Statistics, Volume 18, Issue 1, March 2026.Modal regression. ABSTRACT Modal regression has emerged as a powerful alternative to traditional mean and quantile regression by focusing on estimating the conditional mode rather than the conditional mean or quantiles. This approach offers robustness to outliers and skewed distributions while providing more informative prediction intervals for ...
Sijia Xiang, Weixin Yao, Xinping Cui
wiley +1 more source
Journal of the Society for Information Display, Volume 34, Issue 2, Page 49-67, February 2026.Modern AI systems can now synthesize coherent multimedia experiences, generating video and audio directly from text prompts. These unified frameworks represent a rapid shift toward controllable and synchronized content creation. From early neural architectures to transformer and diffusion paradigms, this paper contextualizes the ongoing evolution of ...
Charles Ding, Rohan Bhowmik
wiley +1 more source
Design Issues for Generalized Linear Models: A Review
, 2006 Generalized linear models (GLMs) have been used quite effectively in the modeling of a mean response under nonstandard conditions, where discrete as well as continuous data distributions can be accommodated.
Ghosh, Malay +3 more
core +3 more sources
Exact Randomized Two‐Stage Phase 2 Clinical Trial Designs for Two Binary Co‐Primary Endpoints
Statistics in Medicine, Volume 45, Issue 3-5, February 2026.ABSTRACT Phase 2 clinical trials typically rely on a single primary endpoint, yet in many settings, treatment efficacy must be demonstrated across multiple co‐primary endpoints. Such settings require intersection‐union hypothesis testing, in which the global null hypothesis is rejected only when all individual component hypotheses are rejected ...
Hyejung Jung +3 more
wiley +1 more source
An Interior-Point algorithm for Nonlinear Minimax Problems [PDF]
We present a primal-dual interior-point method for constrained nonlinear, discrete minimax problems where the objective functions and constraints are not necessarily convex.
B. Rustem, E. Obasanjo, G. Tzallas-Regas
core
CAAI Transactions on Intelligence Technology, Volume 11, Issue 1, Page 15-25, February 2026.ABSTRACT Monge–Ampère equations (MAEs) are fully nonlinear second‐order partial differential equations (PDEs), which are closely related to various fields including optimal transport (OT) theory, geometrical optics and affine geometry. Despite their significance, MAEs are extremely challenging to solve.
Xinghua Pan, Zexin Feng, Kang Yang
wiley +1 more source
Exponential Screening and optimal rates of sparse estimation
, 2010 In high-dimensional linear regression, the goal pursued here is to estimate an unknown regression function using linear combinations of a suitable set of covariates. One of the key assumptions for the success of any statistical procedure in this setup is
Rigollet, Philippe, Tsybakov, Alexandre
core
Adversarial meta-learning of Gamma-minimax estimators that leverage prior knowledge. [PDF]
Electron J Stat, 2023 Qiu H, Luedtke A.
europepmc +1 more source