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 ...
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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 ...
The New York Times

I’m Building an Algorithm That Doesn’t Rot Your Brain

new video loaded: I’m Building an Algorithm That Doesn’t Rot Your Brain transcript “Our brains are being melted by the algorithm.” [MUSIC PLAYING] “Attention is infrastructure.” “Those algorithms are ...
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 ...
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 ...
Scientific Research Publishing

Magoulas, G.D., Vrahatis, M.N. and Androulakis, G.S. (1999) Improving the Convergence of the Backpropagation Algorithm Using Learning Rate Adaptation Methods. Neural ...

ABSTRACT: This paper proposes a unique approach to load forecasting using a fast convergent artificial neural network (ANN) and is driven by the critical need for power system planning. The Mazoon ...
IEEE

COMQ: A Backpropagation-Free Algorithm for Post-Training Quantization

Abstract: Post-training quantization (PTQ) has emerged as a practical approach to compress large neural networks, making them highly efficient for deployment. However, effectively reducing these ...
IEEE

Alpha-Backpropagation Algorithm: Probability Estimation for One-Hot and Quasi-One-Hot Teachers

Abstract: This study proposes theories and applications of probabilistic divergences to neural network training. This theory generalizes the cross-entropy method for backpropagation to the ...