Results 121 to 130 of about 1,570 (213)
Designing Deep Neural Networks through Neuroevolution
This study investigated the designing of deep neural networks using novel neuroevolution models. Advanced algorithms were applied to three real-world problems including energy and medicine applications.
Seyed Mohammad Jafar Jalali (13436616)
core
Direct Evaluation of Treatment Response in Brain Metastatic Disease with Deep Neuroevolution. [PDF]
Stember JN, Young RJ, Shalu H.
europepmc +1 more source
Optimal non-pharmaceutical intervention policy for Covid-19 epidemic via neuroevolution algorithm. [PDF]
Saeidpour A, Rohani P.
europepmc +1 more source
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 algorithms and hardware solutions.
Gabriel Cortês +2 more
openaire +3 more sources
NeuroAction: a neuroevolutionary approach to reinforcement learning for autonomous vehicles. [PDF]
Aboyeji E +3 more
europepmc +1 more source
Complex computation from developmental priors. [PDF]
Barabási DL +3 more
europepmc +1 more source
Leveraging network motifs to improve artificial neural networks. [PDF]
Zhang H +6 more
europepmc +1 more source
Neuroevolution algorithm neat on graphics cards
V magistrski nalogi naslavljamo problem implementacije algoritma NeuroEvolution of Augmenting Topologies (NEAT) za delovanje na grafičnih karticah. Algoritem NEAT je genetski algoritem za učenje razvijajočih nevronskih mrež.
Sitar, Blaž
core
Reinforcement learning of a biflagellate model microswimmer. [PDF]
Bulusu S, Zöttl A.
europepmc +1 more source
Editorial: Marine invertebrates: neurons, glia, and neurotransmitters
Tatiana N. Olivares-Bañuelos +1 more
doaj +1 more source

