Silicon Valley's next risky self-optimization craze is unproven peptides

For many of these uses, the scientific backing is far weaker than that for GLP-1 drugs. Yet many users extrapolate from the ...
GitHub

Hierarchical Patch Based Transformer with Learnable Weighted Loss Optimization for Multivariate Time Series Forecasting (HPBTF)

Forecasting, a fundamental task in machine learning, involves predicting future values of a time series based on its historical behavior. This paper introduces a novel Hierarchical Patch Based ...
ccr-mag

MicroCloud Hologram Unveils Hybrid Quantum-Classical Breakthrough

MicroCloud Hologram Inc. (NASDAQ: HOLO), (“HOLO” or the “Company”), a technology service provider, proposed a Quantum Convolutional Neural Network (QCNN) based on hybrid quantum-classical learning and ...
KRON4 News

MicroCloud Hologram Inc. Releases Hybrid Quantum-Classical Convolutional Neural Network, Achieving New Breakthrough in MNIST Multi-Class Classification

SHENZHEN, China, Oct. 24, 2025 (GLOBE NEWSWIRE) -- MicroCloud Hologram Inc. (NASDAQ: HOLO), (“HOLO” or the "Company"), a technology service provider, proposed a Quantum Convolutional Neural Network ...
Frontiers

Two-layer optimization model of distribution network line loss considering the uncertainty of new energy access

The integration of a distributed generator (DG) into the distribution network alters the topology structure and power flow distribution, subsequently causing changes in network loss. Moreover, ...
Frontiers

Comprehensive benefit optimization method for photovoltaic inverters participating in distribution network loss reduction by reactive compensation

1 School of Mechanical and Electrical Engineering, China University of Mining and Technology-Beijing, Beijing, China 2 State Grid Gansu Electric Power Co., Electric Power Research Institute, Lanzhou, ...
Scientific Research Publishing

Arctic Puffin Optimization Algorithm Based on Multi-Strategy Blending ()

A hybrid strategy is proposed to solve the problems of poor population diversity, insufficient convergence accuracy and susceptibility to local optimal values in the original Arctic Puffin ...
GitHub

KeivanShariatmadar/GSA-Power_Loss_Optimization

MATPOWER is a package of M-files for solving power flow, continuation power flow and optimal power flow problems using MATLAB or Octave. It is intended as a simulation tool for researchers and ...
IEEE

Reinforcement Learning-Based Formulations With Hamiltonian-Inspired Loss Functions for Combinatorial Optimization Over Graphs

Abstract: Quadratic Unconstrained Binary Optimization (QUBO) is a versatile approach used to represent a wide range of NP-hard Combinatorial Optimization (CO) problems through binary variables. The ...