Communications of the ACM

Building Intelligent Agents with Neuro-Symbolic Concepts

The agent acquires a vocabulary of neuro-symbolic concepts for objects, relations, and actions, represented through a ...
Electronics For You

Memristor Training Cuts AI Energy Costs

Chinese researchers harness probabilistic updates on memristor hardware to slash AI training energy use by orders of magnitude, paving the way for ultra-efficient electronics.

Can AI have a positive impact on creative industries? This author thinks so

Jason Van Tatenhove, a journalist, author and former member of extremist group The Oath Keepers, says AI tools have made him ...
Tech Xplore

New memristor training method slashes AI energy use by six orders of magnitude

In a Nature Communications study, researchers from China have developed an error-aware probabilistic update (EaPU) method ...
IEEE

Research on Wafer CMP Temperature Online Detection Compensation Algorithm Based on GA-BP Improved Neural Network

Abstract: In chemical mechanical polishing (CMP), temperature is a primary factor that determines the rate of chemical reactions, which directly influences the polishing efficiency and quality of ...

WiMi Studies Quantum Hybrid Neural Network Model to Empower Intelligent Image Classification

WiMi Studies Quantum Hybrid Neural Network Model to Empower Intelligent Image Classification BEIJING, Jan. 15, 2026––WiMi Hologram Cloud Inc. (NASDAQ: WiMi) ("WiMi" or the "Company"), a leading global ...
Hosted on MSN

Backpropagation in neural networks step-by-step explained

Understand the Maths behind Backpropagation in Neural Networks. In this video, we will derive the equations for the Back Propagation in Neural Networks. In this video, we are using using binary ...
SlashGear

A New Algorithm Beats Dijkstra's Time For The Shortest Path To Any Point In A Network

When Edsger W. Dijkstra published his algorithm in 1959, computer networks were barely a thing. The algorithm in question found the shortest path between any two nodes on a graph, with a variant ...
Frontiers

A total organic carbon prediction algorithm for heterogeneous shale based on interpretable neural network: a case study of Qiongzhusi Formation shale in the Sichuan Basin

Total Organic Carbon (TOC) is a fundamental parameter for evaluating source rock quality, yet the strong heterogeneity of the Qiongzhusi Formation shale reservoir in the Sichuan Basin severely limits ...
Scientific Research Publishing

Hecht-Nielsen (1989) Theory of the Backpropagation Neural Network. International Joint Conference on Neural Networks, New York, 18-22 June 1989, 593-605.

ABSTRACT: The accurate prediction of backbreak, a crucial parameter in mining operations, has a significant influence on safety and operational efficiency. The occurrence of this phenomenon is ...
Scientific Research Publishing

Li, M. (2024) Comprehensive Review of Backpropagation Neural Networks. Academic Journal of Science and Technology, 9, 150-154.

ABSTRACT: The accurate prediction of backbreak, a crucial parameter in mining operations, has a significant influence on safety and operational efficiency. The occurrence of this phenomenon is ...
Frontiers

Enhancing dissolved oxygen prediction in lake-reservoirs via a hybrid BO+SSA-driven backpropagation neural network

With the self-purification ability of lake-reservoir water body gradually weakened and the oscillation of dissolved oxygen (DO) concentration intensifying, the high-precision prediction of ...