network depth

1 statements across 1 episodes · 1 bullish · 0 bearish · 1 people on the record · first statement Dec 31, 2025 by Ishan Gaur · across every show →

Everything said about network depth, oldest first

Dec 31, 2025 positive
Assertion Supported
Gaur: Scaling depth is more parameter- and sample-efficient than width in RL
“But when you look at the number of parameters that your network has as you grow with, it's roughly a quadratic as opposed to something like growing depth, so it's more, in some sense, it's more parameter efficient, also more sample efficient from the experimen…”
Ishan Gaur Dec 31, 2025 ▶ 6:42 [NeurIPS Best Paper] 1000 Layer Networks for Self-Supervised RL — Kevin Wang et al, Princeton
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