AI tracks missing hydrogen atoms in crystals with 97% success rate

Artificial intelligence is often used to generate images. In research, specialized AI models are used for scientific ...
Scientific American

The million-dollar race to ‘blow up’ math’s hardest equations

These are math’s most famous open questions. Solve one, and you’ll win a $1-million prize—but it’s only happened once since ...
C&EN

Ab Initio Nonadiabatic Dynamics of Multichromophore Complexes: A Scalable Graphical-Processing-Unit-Accelerated Exciton Framework

§ School of Chemistry, University of Bristol, Bristol BS8 1TS, U.K. ∥ Department of Computer Science, University of Bristol, Bristol BS8 1UB, U.K. Article Views are the COUNTER-compliant sum of full ...
PNAS

Codiscovering graphical structure and functional relationships within data: A Gaussian Process framework for connecting the dots

Many complex data analysis problems within and beyond the scientific domain involve discovering graphical structures and functional relationships within data. Nonlinear variance decomposition with ...
IEEE

Two New Algorithms for Maximum Likelihood Estimation of Sparse Covariance Matrices With Applications to Graphical Modeling

Abstract: In this paper, we propose two new algorithms for maximum-likelihood estimation (MLE) of high dimensional sparse covariance matrices. Unlike most of the state-of-the-art methods, which either ...
UCL

Gatsby Bridging Programme

An intensive, fast-paced summer school for predoctoral students to build mathematical intuitions and skills necessary to enter the fields of theoretical neuroscience and foundational machine learning ...
Europe PMC

Current Challenges and Future Promise for Use of Extracellular Matrix Scaffold to Achieve the Whole Organ Tissue Engineering Moonshot.

Whole organ tissue engineering encompasses a variety of approaches, including 3D printed tissues, cell-based self-assembly, and cellular incorporation into synthetic or xenogeneic extracellular matrix ...
Frontiers

An Augmented High-Dimensional Graphical Lasso Method to Incorporate Prior Biological Knowledge for Global Network Learning

Biological networks are often inferred through Gaussian graphical models (GGMs) using gene or protein expression data only. GGMs identify conditional dependence by estimating a precision matrix ...