Beyond ICA: Identifiability by Symmetry Breaking

arXiv:2607.23182 · stat.ML, cs.LG, math.ST · Submitted 2026-07-25 · Read on arXiv

Pengzhou Wu

stat.ML, cs.LG, math.ST

Submitted: 2026-07-25

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Terminology

• Decoder — 31× in this paper · explained in 2 episodes
• Generator — 9× in this paper · explained in 2 episodes
• Sparsity — 7× in this paper · explained in 5 episodes
• Generative Model — 6× in this paper · explained in 2 episodes
• Generative Models — 6× in this paper · explained in 3 episodes
• Conditional Independence — 5× in this paper · explained in 2 episodes
• Symmetry Breaking — 4× in this paper · explained in 4 episodes
• Causal Discovery — 3× in this paper · explained in 3 episodes
• Consistency — 3× in this paper · explained in 3 episodes
• Disentanglement — 3× in this paper · explained in 2 episodes
• Equivariance — 3× in this paper · explained in 3 episodes
• Representation Learning — 3× in this paper · explained in 3 episodes
• Downstream Tasks — 2× in this paper · explained in 2 episodes
• Gaussian Mixture Model (GMM) — 2× in this paper · explained in 2 episodes
• Hybrid System — 2× in this paper · explained in 2 episodes
• Latent Space — 2× in this paper · explained in 7 episodes
• Latent Variables — 2× in this paper · explained in 2 episodes
• Abstraction — 1× in this paper · explained in 1 episode
• Adam — 1× in this paper · explained in 3 episodes
• Bayesian Inference — 1× in this paper · explained in 6 episodes
• Causal Inference — 1× in this paper · explained in 5 episodes
• Computational Biology — 1× in this paper · explained in 2 episodes
• Core — 1× in this paper · explained in 2 episodes
• Degeneracy — 1× in this paper · explained in 4 episodes
• Domain Adaptation — 1× in this paper · explained in 5 episodes
• Editor — 1× in this paper · explained in 2 episodes
• Entanglement — 1× in this paper · explained in 5 episodes
• Feature Extraction — 1× in this paper · explained in 3 episodes
• Generalization — 1× in this paper · explained in 14 episodes
• Independent Causal Mechanisms — 1× in this paper
• Latent Dynamics — 1× in this paper · explained in 2 episodes
• Modularity — 1× in this paper · explained in 9 episodes
• Non-Gaussianity — 1× in this paper · explained in 3 episodes
• Papers — 1× in this paper · explained in 3 episodes
• ReLU Network — 1× in this paper · explained in 2 episodes
• Unified Framework — 1× in this paper · explained in 6 episodes
• Unsupervised Learning — 1× in this paper · explained in 2 episodes

Sources

• Interaction Asymmetry: A General Principle for Learning Composable Abstractions
• Towards a Definition of Disentangled Representations
• Mechanistic Independence: A Principle for Identifiable Disentangled Representations
• Identifiability of Potentially Degenerate Gaussian Mixture Models With Piecewise Affine Mixing

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