Mathematics

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Broadcasting

Broadcasting is the set of rules that lets element-wise operations (addition, subtraction, multiplication, division) act on arrays or tensors of different but compatible shapes by virtually stretching the…

Deep Learning Machine Learning

Convolution

Convolution is a mathematical operation that combines two functions to produce a third function, expressing how the shape of one is modified by the other.

Deep Learning Machine Learning

Cross-Entropy

Cross-entropy is a measure from information theory of how many bits (or nats) are needed to encode data drawn from a true probability distribution P when using a code optimized for a different

Deep Learning Machine Learning

Geometric Deep Learning

Geometric deep learning (GDL) is an area of deep learning that designs neural networks around the structure and symmetries of their data.

AI for Science Deep Learning

Inductive bias

Inductive bias (also called learning bias) is the set of assumptions that a learning algorithm uses to predict outputs for previously unseen inputs.

Deep Learning Machine Learning

Manifold Hypothesis

The manifold hypothesis is the conjecture that real-world high-dimensional data, such as natural images, speech, and text representations, concentrates on or near a manifold of much lower dimension embedded…

Deep Learning Machine Learning

Matrix multiplication

Matrix multiplication combines an M by K matrix A with a K by N matrix B to produce an M by N matrix C

AI Hardware Algorithms

Sigmoid Function

The sigmoid function is a mathematical function that maps any real number to a value between 0 and 1 using the formula $$\sigma(x) = \frac{1}{1 + e^{-x}}$$, producing a smooth S-shaped curve.

Deep Learning Machine Learning

Tensor

In machine learning, a tensor is a multi-dimensional array of numbers that serves as the fundamental data structure for representing and manipulating data.

Deep Learning Machine Learning

Tensor Shape

A tensor shape is a tuple of integers that describes the number of elements along each dimension (or axis) of a tensor.

Deep Learning Machine Learning

Wasserstein GAN (WGAN)

A Wasserstein GAN (WGAN) is a generative adversarial network that trains its two networks to minimise the Wasserstein-1 distance, also called the Earth mover's distance, between the real data distribution and…

Deep Learning Generative AI