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I find it hard to write about actual trees in a paper/ grant we are currently working on. Trees are so common to comp/neuro and ML that it is hard to see trees as having green leaves as opposed to structures where vertices are connected by exactly one path.
Sounds like exciting stuff? What are you working on? A project I worked on employed non-paremetrix images registration to hyperspectral images, photos and LiDAR data, collected by drones, to predict biodiversity of forests. You could to do cooler stuff today with modern ML.
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Generative models of dendritic trees. Comparison to trees to inspire the search for concepts.
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Would this be useful reading? If I wanted to learn more? https://neuronaldynamics.epfl.ch/online/Ch3.S2.html …
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