Deep Invertible Autoencoders for Dimensionality Reduction of Dynamical Systems

arXiv:2603.13496 · cs.LG · Submitted 2026-03-13 · Read on arXiv

cs.LG

Submitted: 2026-03-13

Updated: 2026-09-15

DOI: 10.1016/j.cma.2026.119346

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

Terminology

• Accuracy — 6× in this paper · explained in 1 episode
• Activation Function — 3× in this paper · explained in 1 episode
• Generative Model — 3× in this paper · explained in 2 episodes
• Generative Models — 3× in this paper · explained in 2 episodes
• Regularization — 3× in this paper · explained in 3 episodes
• AdamW Optimizer — 2× in this paper · explained in 1 episode
• Approximation Bound — 2× in this paper · explained in 1 episode
• Inverse Problem — 2× in this paper · explained in 2 episodes
• Latent Space — 2× in this paper · explained in 7 episodes
• Normalizing Flow — 2× in this paper · explained in 3 episodes
• Normalizing Flows — 2× in this paper · explained in 4 episodes
• Adaptation — 1× in this paper · explained in 1 episode
• Core — 1× in this paper · explained in 2 episodes
• Decode — 1× in this paper · explained in 2 episodes
• Domain Adaptation — 1× in this paper · explained in 5 episodes
• Generalization — 1× in this paper · explained in 13 episodes
• Generative Modeling — 1× in this paper · explained in 3 episodes
• Intrinsic Dimension — 1× in this paper · explained in 2 episodes
• Loss Function — 1× in this paper · explained in 2 episodes
• Objective Function — 1× in this paper · explained in 2 episodes
• Reconstruction Error — 1× in this paper · explained in 2 episodes
• Reinforcement Learning — 1× in this paper · explained in 4 episodes
• Robustness — 1× in this paper · explained in 5 episodes
• Singular Value Decomposition (SVD) — 1× in this paper · explained in 2 episodes
• Theoretical Guarantees — 1× in this paper · explained in 2 episodes
• Uncertainty Quantification — 1× in this paper · explained in 8 episodes

Sources

• Deep Symmetric Autoencoders from the Eckart-Young-Schmidt Perspective
• NICE: Non-linear Independent Components Estimation
• Guided Image Generation with Conditional Invertible Neural Networks
• Analysis of Invariance and Robustness via Invertibility of ReLU-Networks
• Adversarial Spheres

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