The Modern Mathematics of Deep Learningexplained for non-mathematicians

A PDE solution and initial condition

Penguin learning project

The project uses 342 complete Palmer penguin records: 240 training-pool and 102 held-out rows. The selected training rows determine feature scaling and model parameters. Source CSV

This project trains weights with softmax, unlike the homepage lab, which uses nearest species averages. Same penguin measurements; different classification methods. Predictions can differ.

PDE and stochastic processes · Describe differential equations and stochastic representations.

PDE and quantum models are not operations on these penguin measurements.

Consider this concept alongside the project; its source assumptions may differ. These observations do not prove a theorem.

Input: 12 × 2; Held-out evaluation: 102 · #58 · 40.6 mm, 193 mm. Known answer: Adélie; Prediction: Adélie · [≈0.7383, ≈0.2444, ≈0.01737].

Used in these source sections: 4.3 Structure from an equation

g(x,t) is the solution at position x and time t. At a fixed time, g(·,t) is a function of position.

A time-dependent solution assigns a value to each position and time.

Source formula example

gg

illustration · This quadratic solves ∂ₜg = (1/2)∂ₓₓg with zero drift and unit stochastic diffusion σ = 1; it is not the general source solution.

Symbols

gg
A PDE solution.
xx
A position.
tt
A time.
g(⋅,t)g(·,t)
The solution as a function of position at fixed t.

Source formula example

This source example uses its own inputs and assumptions. Editing it does not change the project.

Edit a value or the code, then run the example. This is a finite demonstration, not a proof of the paper’s theorem.

This example’s data flow

Initial values in code

  • x = 2
  • t = 1

Calculated here

Result expression: { x, t, value: g(x, t), initial: g(x, 0) }

Returns

Example result
x
2
t
1
value
5
initial
4

Read numbers from input and return the result. JavaScript basics.

Result

Enable JavaScript to run this example.

Technical statement

The numerical values are invented unless the source values are stated. This quadratic solves ∂ₜg = (1/2)∂ₓₓg with zero drift and unit stochastic diffusion σ = 1; it is not the general source solution.

Source: Inline notation