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Found 4 papers, 3 papers with code
EvoGP: A GPU-accelerated Framework for Tree-based Genetic Programming
However, GPU acceleration of TGP faces three key challenges: inefficient tree encoding, highly heterogeneous genetic operations, and limited parallelism in fitness evaluation.
Towards Scalable GPU-Accelerated SNN Training via Temporal Fusion
Drawing on the intricate structures of the brain, Spiking Neural Networks (SNNs) emerge as a transformative development in artificial intelligence, closely emulating the complex dynamics of biological neural networks.
Tensorized NeuroEvolution of Augmenting Topologies for GPU Acceleration
Through evaluations across a spectrum of robotics control environments in Brax, TensorNEAT achieves up to 500x speedups compared to the existing implementations such as NEAT-Python.
GPU-accelerated Evolutionary Multiobjective Optimization Using Tensorized RVEA
Evolutionary multiobjective optimization has witnessed remarkable progress during the past decades.
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