Research map / Probabilistic and scientific modeling / Variational and generative sampling
Estimating the Unique Information of Continuous Variables
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 changed | Where | Measured | Effect |
|---|---|---|---|
| Increase generalized XOR task difficulty | Recurrently trained neural networks · Generalized XOR, K in {4,6,8,10} | Average PID terms S, R, and U | Helped |
| Use networks with grandmother-cell-like receptive fields rather than distributed mixed-selectivity representations | Generalized XOR recurrent networks · Generalized XOR classification | Unique information relative to synergy | Mixed |
| Estimate continuous PID with the copula-based method | Three-dimensional Gaussian distributions · Gaussian unique-information comparison | Unique information agreement with exact solution | Helped |
Closest papers by meaning
- Analytically deriving Partial Information Decomposition for affine systems of stable and convolution-closed distributions (NeurIPS 2024 · similarity 0.91)
- Partial Information Decomposition via Normalizing Flows in Latent Gaussian Distributions (NeurIPS 2025 · similarity 0.88)
- Neural Mutual Information Estimation with Vector Copulas (NeurIPS 2025 · similarity 0.86)
- Mutual Information Estimation via $f$-Divergence and Data Derangements (NeurIPS 2024 · similarity 0.85)
- MINDE: Mutual Information Neural Diffusion Estimation (ICLR 2024 · similarity 0.85)
- InfoNet: Neural Estimation of Mutual Information without Test-Time Optimization (ICML 2024 · similarity 0.84)
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.
