Notes tagged with "modeling": Nonlinear Function

16 notes tagged with "modeling"

Black-Scholes

A model of [ option ] prices that assumes: The existence of a risk-free asset paying some interest rate, for example, US Treasury bonds…

Tagged with: #finance#math#modeling

agent

see also [ agency ]

Tagged with: #ai#modeling

all models are wrong

Fundamental observation is that [ the map is not the territory ]. BUT---there is a real and important distinction between models that are…

Tagged with: #modeling

calibration

Tagged with: #modeling#machine-learning

energy-based model

Tagged with: #machine-learning#modeling

flexible model family

As AGW points out here , it is statistically better to fit a flexible model family, with an inductive bias, than a constrained model family…

Tagged with: #machine-learning#modeling

it's hard not to learn from experience

It can be very hard to hold onto a positive self-image and an [ optimism|optimistic ] worldview, even if you intellectually 'know' these to…

Tagged with: #personal#growing-up#mental-health#modeling

large models

If you believe that neural nets basically just memorize the training data, then training larger and larger models is hopeless. The…

Tagged with: #modeling#machine-learning

many models

An idea I got from [ John Higgs ]'s discussion of metamodernism is that taking [ all models are wrong ] to its logical conclusion requires…

Tagged with: #modeling#ai#how-to-think

mental models

One last thought mental models are so, so important. When I think about computer modeling. It's actually great computers are powerful they…

Tagged with: #modeling#how-to-think

multivariate time series

[ thoughts on multivariate causalimpact ]

Tagged with: #modeling#bayes

phase change hypothesis

(see also: [ large models ]) There's a viewpoint that neural nets just memorize the training data, so the more training data you have, the…

Tagged with: #machine-learning#modeling

probabilistic programming

Tagged with: #machine-learning#modeling

probabilities hide detail

Matt Levine explains how a financier might react to losing a billion dollars: Sure sure the risks didn’t work out but you probably have a…

Tagged with: #modeling

product of experts

Introduced by Geoff Hinton (1999): Products of Experts . Each expert produces a probability distribution. These are combined by…

Tagged with: #math#machine-learning#modeling

reality tunnel

Tagged with: #drugs#modeling

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