Nature

Predicting protein function from sequence and structure

'Inheritance through homology' is the most common and generally more accessible approach to function prediction, but orthology should be established where possible to improve confidence in predictions ...
Investopedia

Understanding Utility Functions: Definition, Calculation, and Examples

Andriy Blokhin has 5+ years of professional experience in public accounting, personal investing, and as a senior auditor with Ernst & Young. Erika Rasure is globally-recognized as a leading consumer ...
GitHub

CPM_n_folds_permutation_p_value.m

function [pval_pos, pval_neg, pval_both, prediction_r] = CPM_n_folds_permutation_p_value (no_iterations, R_pos_repeat, R_neg_repeat, R_both_repeat, R_pos_permutation ...
IEEE

Quadrature Permutation Matrix Modulation

Abstract: This paper introduces the in-phase and quadrature (IQ) extension to the permutation matrix modulation (PMM) technique and proposes the quadrature PMM (QPMM) scheme for higher spectral ...
IEEE

Rotation- and Permutation-Equivariant Quantum Graph Neural Network for 3D Graph Data

Abstract: Equivariant quantum graph neural networks (EQGNNs) offer a potentially powerful method to process graph data. However, existing EQGNN models only consider the permutation symmetry of graphs, ...
GitHub

Explainable ML for Low-Emission Methane Tri-Reforming

An Aspen Plus Gibbs free-energy-minimization model generates a 46,464-point tri-reforming (TRM) equilibrium dataset. Decision-tree, random-forest, XGBoost, and artificial-neural-network (ANN) ...