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📐Linear Algebra15📈Calculus & Differentiation10🎯Optimization14🎲Probability Theory12📊Statistics for ML9📡Information Theory10🔺Convex Optimization7🔢Numerical Methods6🕸Graph Theory for Deep Learning6🔵Topology for ML5🌐Differential Geometry6∞Measure Theory & Functional Analysis6🎰Random Matrix Theory5🌊Fourier Analysis & Signal Processing9🎰Sampling & Monte Carlo Methods10🧠Deep Learning Theory12🛡️Regularization Theory11👁️Attention & Transformer Theory10🎨Generative Model Theory11🔮Representation Learning10🎮Reinforcement Learning Mathematics9🔄Variational Methods8📉Loss Functions & Objectives10⏱️Sequence & Temporal Models8💎Geometric Deep Learning8

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📚TheoryIntermediate

Minimum Description Length (MDL)

Minimum Description Length (MDL) picks the model that compresses the data best by minimizing L(M) + L(D|M).

#minimum description length#mdl#bic+12
📚TheoryIntermediate

Grokking & Delayed Generalization

Grokking is when a model suddenly starts to generalize well long after it has already memorized the training set.

#grokking#delayed generalization
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Filtering by:
#minimum description length
#weight decay
+12
📚TheoryAdvanced

Algorithmic Information Theory

Algorithmic Information Theory studies information content via the shortest programs that generate data, rather than via average-case probabilities.

#kolmogorov complexity#algorithmic probability#solomonoff induction+11