Ishan Gaur

Everything Ishan Gaur said on any show that made the record, most notable first. Each card names its show and opens the statement there.

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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

The other half of the tape: Ishan Gaur's own voice is left out of every number here. 1 statement on the record names them. every mention, with the transcript →

Statements about Ishan Gaur, by other people (1)

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Eysenbach: Scaling RL depth requires combining depth with residual connections

“And if we just made the depth bigger, it makes it worse. If we just add residual connections, it didn't make it better. And it was really this combination of factors that Kevin and Ishan figured out that really made this work.”

Benjamin Eysenbach Dec 31, 2025 ▶ 5:56 [NeurIPS Best Paper] 1000 Layer Networks for Self-Supervised RL — Kevin Wang et al, Princeton

One line per show, most statements first. The link opens Ishan's full record on that show: the calibration, argument clarity, speaking style and every statement made there.

Show	Role there	Eps	Statements	Record
LATENT SPACELEDGER		1	1	100% 1/1	full record on Latent Space →