Gaussian noise
Gaussian noise is random variation whose values follow a Gaussian, or normal, probability distribution.
Deep Learning with JAX
Random noise with a Gaussian distribution added to data, here used to simulate image corruption.
- How it is used
- Augments images by simulating corruption or producing additional noisy training examples.
- How deep it goes
- Explains generation, scaling, addition, and normalization, while deferring detailed PRNG internals.
- Examples
- Uses camera-noise simulation, cat-and-dog augmentation, a shaped image tensor, and a normalized noisy image.
- What you can do after
- Apply it via JAX or scikit-image to generate, add, and normalize Gaussian noise for image augmentation.
Inside Deep Learning: Math, Algorithms, Models
Random perturbation sampled from a Gaussian distribution and added to data or activations to simulate noise.
- How it is used
- Uses perturbations to train denoising autoencoders that reconstruct clean inputs and learn robust representations.
- How deep it goes
- Explains the motivation and module placement but defers the Gaussian sampling formula and noise-scale selection details.
- Examples
- Demonstrates noisy OCR-like images, additive-noise autoencoders, and comparisons between clean, Gaussian-noisy, and dropout-noisy inputs.
- What you can do after
- Apply it via a training-only PyTorch noise module inside a denoising autoencoder.
Read how Inside Deep Learning: Math, Algorithms, Models explains Gaussian noise →
Grokking AI Algorithms, Second Edition
Gaussian noise is random variation whose values follow a Gaussian probability distribution.
- How it is used
- Uses predictable random variation to create training pairs for image diffusion models.
- How deep it goes
- Defines standard-normal sampling, explains its probability pattern, and implements progressive image noising with stored noise patterns.
- Examples
- Demonstrates Gaussian noise through progressively noisier images, probability-distribution visualization, and Python diffusion code.
- What you can do after
- Apply it via a forward-diffusion implementation that samples, scales, mixes, and records noise for model training.
Read how Grokking AI Algorithms, Second Edition explains Gaussian noise →
Related concepts
- embeddinguses · A numerical vector representation of an item or input that encodes features or relationships useful for computational tasks.
- noisekind of · Noise is variation, content, or data treated as unwanted, irrelevant, or distinct from the signal, pattern, or structure of interest.
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