Overview

Parameter identifiability asks whether different parameter values or models can produce the same observations, and which aspects of a system can therefore be recovered. Researchers analyze symmetries and equivalence classes, use rank and Fisher-information conditions, and design informative experiments with sufficient excitation, diverse trajectories, or interventions. These ideas apply to dynamical systems, inverse problems, latent-variable models, and neural networks, where tools such as structural analysis, Bayesian inference, and constrained estimation help distinguish unique recovery from uncertainty or partial identification. A central tension is that accurate predictions do not guarantee uniquely or precisely identified parameters: structural ambiguities may persist regardless of data volume, while finite, noisy data can make even identifiable parameters difficult to estimate.

Latest papers

CardsList

103 papers13 papers in the last four weeks, up 160% on the four weeks before. 0.1% of all new papers.

  1. Provable Subspace Identification of Nonlinear Multi-view CCA

    Feb 27, 2026Zhiwei Han, Stefan Matthes, Hao ShenRepresentation IdentifiabilityParameter Identifiability

  2. PHAST: Port-Hamiltonian Architecture for Structured Temporal Dynamics Forecasting

    Feb 20, 2026Shubham Bhardwaj, Chandrajit BajajTime Series ForecastingPort-Hamiltonian Systems

  3. Stability and Concentration in Nonlinear Inverse Problems with Block-Structured Parameters: Lipschitz Geometry, Identifiability, and an Application to Gaussian Splatting

    Feb 10, 2026Joe-Mei Feng, Hsin-Hsiung KaoInverse RenderingParameter Identifiability

  4. Complete Identification of Deep ReLU Networks through Łukasiewicz Logic

    Jan 30, 2026Yani Zhang, Helmut BölcskeiParameter IdentifiabilityReLU Neural Networks

  5. Uncertainty-aware Causal Decision Making via Effect Bound Decomposition

    Jan 30, 2026Md Musfiqur Rahman, Ziwei Jiang, Hilaf Hasson +1Causal Effect EstimationParameter Identifiability

  6. Nonnegative matrix factorizations and related compositional models: Equivalence, identifiability, and an application on the grain-size analysis of sediments

    Dec 25, 2025Qianqian Qi, Peter G. M. van der Heijden, Maarten A. PrinsLatent Variable ModelsParameter Identifiability

  7. Variational Physics-Informed Ansatz for Reconstructing Hidden Interaction Networks from Steady States

    Dec 6, 2025Kaiming LuoParameter Identifiability

  8. Provable Affine Identifiability of Nonlinear CCA under Latent Distributional Priors

    Oct 6, 2025Zhiwei Han, Stefan Matthes, Hao ShenRepresentation LearningParameter Identifiability

  9. Identifiable Convex-Concave Regression via Sub-gradient Regularised Least Squares

    Jun 22, 2025William ChungParameter IdentifiabilityNonparametric Regression

  10. Identifiability Analysis of Linear ODE Systems with Hidden Confounders

    Oct 29, 2024Yuanyuan Wang, Biwei Huang, Wei Huang +2Parameter IdentifiabilityCausal Identifiability

  11. Epsilon-Identifiability of Causal Quantities

    Jan 27, 2023Ang Li, Scott Mueller, Xin Shu +1Causal IdentifiabilityCausal Inference

  12. Symbolic Recovery of Differential Equations: The Identifiability Problem

    Oct 15, 2022Philipp Scholl, Aras Bacho, Holger Boche +1Parameter IdentifiabilityAutonomous Scientific Discovery