145 citations · 564 across the 20 of their papers we have counts for
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cs.NE2018★ 15 cited
Learning concise representations for regression by evolving networks of trees
William La Cava, Tilak Raj Singh, James Taggart +2
We propose and study a method for learning interpretable representations for the task of regression. Features are represented as networks of multi-type expression trees comprised o…
cs.NE2018★ 145 cited
Where are we now? A large benchmark study of recent symbolic regression methods
Patryk Orzechowski, William La Cava, Jason H. Moore
In this paper we provide a broad benchmarking of recent genetic programming approaches to symbolic regression in the context of state of the art machine learning approaches. We use…