A.I.’s First Big Math Breakthrough Is Not What It Seems

Last month, OpenAI announced that its latest version of ChatGPT had solved a major math problem, one that had stumped experts ...
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 ...
Nature

The analysis of deep reinforcement learning for dynamic graphical games under artificial intelligence

This paper explores the use of deep reinforcement learning (DRL) to enable autonomous decision-making and strategy optimization in dynamic graphical games. The proposed approach consists of several ...
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 ...
Frontiers

Applying risk matrices for assessing the risk of psychosocial hazards at work

Although wide-ranging amendments in health and safety regulations at the European and national level oblige employers to conduct psychosocial risk assessment, it is still under debate how psychosocial ...
Nature

Quantum computing formulation of some classical Hadamard matrix searching methods and its implementation on a quantum computer

Finding a Hadamard matrix (H-matrix) among all possible binary matrices of corresponding order is a hard problem that can be solved by a quantum computer. Due to the limitation on the number of qubits ...
IEEE

Comparing Different Approaches for Solving Large Scale Power-Flow Problems With the Newton-Raphson Method

Abstract: This paper focuses on using the Newton-Raphson method to solve the power-flow problems. Since the most computationally demanding part of the Newton-Raphson method is to solve the linear ...
Scientific Research Publishing

A Novel Method for Solving Ordinary Differential Equations with Artificial Neural Networks ()

This research work investigates the use of Artificial Neural Network (ANN) based on models for solving first and second order linear constant coefficient ordinary differential equations with initial ...