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Writing study: Filtered Conformal Ellipsoids for Graph-Native Time Series

← NeurIPS 2026 oral writing corpus

Yannick Limmer · Official NeurIPS 2026 oral record

Figure, table and section ledger

Editorial contribution type: Theory & formal analysis (primary).

Layout extraction, not a required paper template. Counts are distinct caption labels; a multi-panel figure counts once. Section spans are estimated from heading positions, including floats and whitespace. Method and limitations.

Canonical PDF
45 physical pages
Before references / appendix
≈ 10.33 page-equivalents
Main figures / tables
2 / 3
Attached appendix figures / tables
1 / 22
Attached appendix span
≈ 32.91 page-equivalents
Before references / appendix: ≈ 22.96%References / intervening material: ≈ 3.91%Attached appendix: ≈ 73.13%Estimated layout envelopes, not text/artwork area. Unresolved appendix boundaries remain within the undivided post-body material.

Source-bound correction: Top-level heading and reference/appendix boundaries checked against source PDF text. Bibliography titles/author initials, numbered contribution/property bullets, diagram steps, equations and TOC entries are not substantive headings. Section spans are page-coordinate estimates, not ink area or prose-only length. This is an author manuscript mirror, not a verified accepted-version template. Source layout uses physical single-column y/page-height, including equation-heavy pages.

Section-by-section lengths and source pages

The title/abstract/front matter precede the first numbered heading. A span ends at the next detected top-level heading, not at the last sentence; end-page whitespace is included. References and statements are listed separately. These are not measurements of text-only or artwork area.

Top-level headingStarts on PDF pageEstimated spanShare of entire PDF
1 Introduction1≈ 1.37 pp.3.04%
2 Related work3≈ 0.39 pp.0.87%
3 Preliminaries3≈ 1.31 pp.2.91%
4 Filtered conformal prediction4≈ 0.83 pp.1.84%
5 Theory5≈ 2.21 pp.4.91%
6 Experiments7≈ 2.36 pp.5.24%
7 Discussion and limitations10≈ 0.9 pp.2%
Acknowledgments and Disclosure of Funding11≈ 0.23 pp.0.51%
References11≈ 1.77 pp.3.93%
A Observable-contraction theory13≈ 3.61 pp.8.02%
B Full proofs and derivations16≈ 7.73 pp.17.18%
C Filter specifications, training, and pseudocode24≈ 4.15 pp.9.22%
D Baseline implementations28≈ 2.86 pp.6.36%
E Additional experiments31≈ 13.86 pp.30.8%
F Reproducibility45≈ 0.7 pp.1.56%
All detected figure and table locations

Argument and organization

  1. Problem and contribution

    Separates learning an ellipsoid's shape from conformal calibration of its radius, avoiding reliance on Gaussian tail probabilities.

  2. Argument sequence

    Presents construction, conditional theory and three numbered experimental questions before limitations.

  3. Evidence and verification

    The headline table reports coverage next to width, defines the target tolerance and notes native versus shared mean predictors.

Problem, claim and contribution

Separates learning an ellipsoid's shape from conformal calibration of its radius, avoiding reliance on Gaussian tail probabilities.

Introduction; Figure 1 · Main paper

Argument and section order

Presents construction, conditional theory and three numbered experimental questions before limitations.

Sections 4–7 · Main paper

Figures, captions and visual explanation

The five-stage schematic distinguishes frozen filtering, scalar scoring and calibration. Coverage–width panels place a target line beside sharpness.

Figure 1, p. 2; Figure 2, p. 8 · Main paper

Tables, comparisons and evidence

The headline table reports coverage next to width, defines the target tolerance and notes native versus shared mean predictors.

Table 2, p. 8 · Main paper

Appendix and reproducibility

Proofs, algorithms, dataset taxonomy, mean-predictor ledger, per-seed results and assumption diagnostics have explicit sections and tables.

Appendices A–E · Main paper

Clarity and writing conventions

The text repeatedly distinguishes finite-trajectory diagnostics from certification of population assumptions, and retains full-graph non-winning cases.

Table 1; Section 7; Appendix E.15 · Main paper

What to reuse—and what not to infer

Transferable lesson: Place the comparison contract beside the numbers and distinguish empirical checks from proof assumptions.

Boundary: This is not universal full-graph leadership or conditional coverage. The source reports backbone- and scale-dependent limits.

Apply this lesson using the argument and evidence worksheet.

Inspection record and sources

Checked
2026-10-02
Reading status
Writing-focused manuscript scan + selected visuals inspected
Main text
Writing-oriented distributed manuscript scan of Sections 1–7, pp. 1–10; references pp. 11–12: abstract/framing, section sequence, substantive text windows, captions, evidence organization and conclusion; not exhaustive technical verification.
Appendix / supplement
Writing-oriented scan of Appendices A–F, pp. 13–45; proof structure and experiment-ledger scan, not theorem re-derivation; code and experiments were not executed.
Visually inspected PDF pages
2, 8

This is a writing-focused scan of the manuscript and the stated supplementary scope: framing, organization, visual explanation, evidence presentation and wording. It is not a line-by-line proof audit, reproduction of results or exhaustive scientific review.