atlas

Research map / Probabilistic and scientific modeling / Dynamical systems

Learning interpretable continuous-time models of latent stochastic dynamical systems

ICML 2019 · Probabilistic and scientific modeling › Dynamical systems · approach: State-space inference for stochastic systems · 40 citations (OpenAlex)

Read the paperCheck your idea against 108,967 papers

AI-extracted summary. Written by AI from the paper's title only (no summary yet). Numbers and claims can be wrong or missing context, so check the paper before you cite or build on it.

Measured effects reported in the paper

What was changedWhereMeasuredEffect
Account for symmetric variations in the latent covariance matrix (ablation)Variational inference for latent SDEs · Simulated nonlinear dynamical systemsnumerical stabilityHelped

Closest papers by meaning

Writing a paper in this area? scime draft is a free LaTeX editor with AI included, real-time co-authors and a check of your references and venue rules before you submit. It also imports OpenAI Prism projects.

Open scime draft

Get the next scime Dispatch and a monthly field update

Free. We send a confirmation link first; every email has a one-click unsubscribe. Privacy