mlsanityData to 14 Oct 2026

Robust Simulation-Based Inference under Missing Data via Neural Processes

arXiv 2503.01287 ↗First posted 3 Mar 2025cs.LG cs.AI stat.MLcited by 5

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Abstract (arXiv)

Simulation-based inference (SBI) methods typically require fully observed data to infer parameters of models with intractable likelihood functions. However, datasets often contain missing values due to incomplete observations, data corruptions (common in astrophysics), or instrument limitations (e.g., in high-energy physics applications). In such scenarios, missing data must be imputed before applying any SBI method. We formalize the problem of missing data in SBI and demonstrate that naive imputation methods can introduce bias in the estimation of SBI posterior. We also introduce a novel amortized method that addresses this issue by jointly learning the imputation model and the inference network within a neural posterior estimation (NPE) framework. Extensive empirical results on SBI benchmarks show that our approach provides robust inference outcomes compared to standard baselines for varying levels of missing data. Moreover, we demonstrate the merits of our imputation model on two real-world bioactivity datasets (Adrenergic and Kinase assays). Code is available at https://github.com/Aalto-QuML/RISE.

Key facts. Cited by 5 papers in the map (data through 14 Oct 2026). Builds on 49 of its 88 references that are in the map. First posted on arXiv 3 Mar 2025.

Builds on

49 of 88 references.

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Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2025: 4; 2026: 1.

5 papers.

  1. 2025Causal Posterior Estimationcited by 1
  2. 2025Flexible Gravitational-Wave Parameter Estimation with Transformerscited by 1
  3. 2025A Review of Diffusion-based Simulation-Based Inference: Foundations and Applications in Non-Ideal Data Scenarioscited by 1
  4. 2025AD-NODE: Adaptive Dynamics Learning with Neural ODEs for Mobile Robots Controlcited by 0
  5. 2026Overcoming Selection Bias in Statistical Studies With Amortized Bayesian Inferencecited by 0