Results 31 to 40 of about 510 (57)
Towards Physical Plausibility in Neuroevolution Systems
The increasing usage of Artificial Intelligence (AI) models, especially Deep Neural Networks (DNNs), is increasing the power consumption during training and inference, posing environmental concerns and driving the need for more energy-efficient ...
Cortês, Gabriel +2 more
core
Deep Learning-Based Operators for Evolutionary Algorithms
We present two novel domain-independent genetic operators that harness the capabilities of deep learning: a crossover operator for genetic algorithms and a mutation operator for genetic programming.
Elyasaf, Achiya +2 more
core
Neuroevolving Electronic Dynamical Networks
Neuroevolution is a powerful method of applying an evolutionary algorithm to refine the performance of artificial neural networks through natural selection; however, the fitness evaluation of these networks can be time-consuming and computationally ...
Whitley, Derek
core
Differential Evolution with Reversible Linear Transformations [PDF]
, 2020 Eiben, A.E. +2 more
core +1 more source
This study explores the application of evolutionary generative algorithms in music production to preserve and enhance human creativity. By integrating human feedback into Differential Evolution algorithms, we produced six songs that were submitted to ...
Ellis, Caroline, Kilb, Justin
core
CADE: Cosine Annealing Differential Evolution for Spiking Neural Network
Spiking neural networks (SNNs) have gained prominence for their potential in neuromorphic computing and energy-efficient artificial intelligence, yet optimizing them remains a formidable challenge for gradient-based methods due to their discrete, spike ...
Du, Guodong +5 more
core
Some of the next articles are maybe not open access.
Cancer Research, 2022
Background: Incorporation of prior information in the form of pathway activity profiles was key in the success of the algorithm that won the DREAM challenge to predict in vitro cell fitness from transcriptomic and other multi-omic datasets (Costello, C.
Andrew R. Schultz +7 more
semanticscholar +1 more source
Background: Incorporation of prior information in the form of pathway activity profiles was key in the success of the algorithm that won the DREAM challenge to predict in vitro cell fitness from transcriptomic and other multi-omic datasets (Costello, C.
Andrew R. Schultz +7 more
semanticscholar +1 more source
Molecular imaging in oncology: Current impact and future directions
Ca-A Cancer Journal for Clinicians, 2022Martin G Pomper, Steven P Rowe
exaly
Emerging 2D Memory Devices for In‐Memory Computing
Advanced Materials, 2021Jun He, Ruiqing Cheng, Qisheng Wang
exaly
2D Material Based Synaptic Devices for Neuromorphic Computing
Advanced Functional Materials, 2021Chao Zhu, Fucai Liu, Zheng Liu
exaly