Placeholder: [Burroughs' collage style, colourful mathematics finance] Parametric VaR Historical Simulation woman Monte Carlo Simulation Modern Portfolio Theory (MPT) Capital Asset Pricing Model (CAPM) Arbitrage Pricing Theory (APT) Black-Litterman Model Black-Scholes Model Binomial Options Pricing Model Cox-Ross-Rubinstein Model Heston Model (stochastic volatility) Vasicek Model Hull-White Model [Burroughs' collage style, colourful mathematics finance] Parametric VaR Historical Simulation woman Monte Carlo Simulation Modern Portfolio Theory (MPT) Capital Asset Pricing Model (CAPM) Arbitrage Pricing Theory (APT) Black-Litterman Model Black-Scholes Model Binomial Options Pricing Model Cox-Ross-Rubinstein Model Heston Model (stochastic volatility) Vasicek Model Hull-White Model

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Prompt

[Burroughs' collage style, colourful mathematics finance] Parametric VaR Historical Simulation woman Monte Carlo Simulation Modern Portfolio Theory (MPT) Capital Asset Pricing Model (CAPM) Arbitrage Pricing Theory (APT) Black-Litterman Model Black-Scholes Model Binomial Options Pricing Model Cox-Ross-Rubinstein Model Heston Model (stochastic volatility) Vasicek Model Hull-White Model

statue, doubles, twins, entangled fingers, Worst Quality, ugly, ugly face, watermarks, undetailed, unrealistic, double limbs, worst hands, worst body, Disfigured, double, twin, dialog, book, multiple fingers, deformed, deformity, ugliness, poorly drawn face, extra_limb, extra limbs, bad hands, wrong hands, poorly drawn hands, messy drawing, cropped head, bad anatomy, lowres, extra digit, fewer digit, worst quality, low quality, jpeg artifacts, watermark, missing fingers, cropped, poorly drawn

18 days ago

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Model

SSD-1B

Guidance Scale

7

Dimensions

1024 × 1024

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Local and global approaches in mathematics and machine learning are both universal approximators, but they differ in the number of parameters required to represent a given function accurately. The entire system, including data, architecture, and loss function, must be considered, as they are interconnected. Data can be noisy or biased, architecture may demand excessive parameters, and the chosen loss function may not align with the desired goal. To address these challenges, practitioners should
A semiregular tiling of the plane.
The depth of hula groove Moves us to the nth hoop We're gonna groove to Horton Hears a Who-who I couldn't ask for another No, I couldn't ask for another DJ Soul was on a roll I've been told he can't be sold He's not vicious or malicious Just de-lovely and delicious I couldn't ask for another
[art by Jean-Paul Riopelle]
A semiregular tiling of the plane.
A semiregular tiling of the plane.
Imagine having a large collection of books and tapes, but some of them contain errors or biases. These flaws introduce incorrect information and spurious correlations. For example, books with a specific font style might have inaccuracies unrelated to the content. To overcome this, you want to extract the genuine knowledge common to all the books and tapes, disregarding the flawed details. The goal is to find a representation that captures the underlying concepts, free from biases. Similarly, in
[series by Jean-Paul Riopelle] Haunting Echoes of Experimentation
A semiregular tiling of the plane.
The depth of hula groove Moves us to the nth hoop We're gonna groove to Horton Hears a Who-who I couldn't ask for another No, I couldn't ask for another DJ Soul was on a roll I've been told he can't be sold He's not vicious or malicious Just de-lovely and delicious I couldn't ask for another
Sorting Jawas
Regular pentagons do not tile the plane, but there are 15 families of irregular convex pentagons that do

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