# COPA 2025 : 14th Symposium on Conformal and Probabilistic Prediction with Applications

The Conference was held on September 10, 2025. The conference covers research topics in Artificial Intelligence, Uncategorized and Multidisciplinary &amp; General.

**Type**: Conference
**Status**: Expired
**Verified On**: 9th May, 2026

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## ⏱ Critical Deadline
> *No submission deadline specified*

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## 📍 Event Information
- **Mode**: In Person
- **Location**: Global
- **Field**: Interdisciplinary
- **Date**: September 10-12, 2025
- **Official Website**: [https://copa-conference.com/](https://copa-conference.com/?utm_source=callforpaper.org)

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## 📝 Call for Papers Description


<a href="https://callforpaper.org/categories/conomie" title="Browse  call for papers" rel="follow" aria-label="View more  call for papers" class="!text-inherit !font-normal !underline decoration-dotted decoration-slate-400/60 underline-offset-4 cursor-pointer hover:decoration-slate-900 dark:hover:decoration-slate-100 transition-colors"></a>The aim of this <a href="https://callforpaper.org/categories/conference-1" title="Browse conference call for papers" rel="follow" aria-label="View more conference call for papers" class="!text-inherit !font-normal !underline decoration-dotted decoration-slate-400/60 underline-offset-4 cursor-pointer hover:decoration-slate-900 dark:hover:decoration-slate-100 transition-colors">conference</a> is to serve as a forum for the presentation of new and ongoing work and the exchange of ideas between researchers on any aspect of conformal and probabilistic <a href="https://callforpaper.org/categories/prediction" title="Browse prediction call for papers" rel="follow" aria-label="View more prediction call for papers" class="!text-inherit !font-normal !underline decoration-dotted decoration-slate-400/60 underline-offset-4 cursor-pointer hover:decoration-slate-900 dark:hover:decoration-slate-100 transition-colors">prediction</a>, including their <a href="https://callforpaper.org/categories/application-1" title="Browse application call for papers" rel="follow" aria-label="View more application call for papers" class="!text-inherit !font-normal !underline decoration-dotted decoration-slate-400/60 underline-offset-4 cursor-pointer hover:decoration-slate-900 dark:hover:decoration-slate-100 transition-colors">application</a> to interesting problems in any field.<br><br>Conformal prediction (CP) is a modern machine and statistical learning method that allows to develop valid predictions under weak probabilistic assumptions. CP can be used to form set predictions, using any underlying point predictor, and for very general target variables, allowing the error levels to be controlled by the user. CP has been widely used to develop robust forms of probabilistic prediction methodologies, and applied to many practical real life challenges.<br><br>Topics include, but are not limited to:<br><br>- Theoretical analysis of conformal prediction, including performance guarantees and optimality results.<br>- <a href="https://callforpaper.org/categories/applications-1" title="Browse Applications call for papers" rel="follow" aria-label="View more Applications call for papers" class="!text-inherit !font-normal !underline decoration-dotted decoration-slate-400/60 underline-offset-4 cursor-pointer hover:decoration-slate-900 dark:hover:decoration-slate-100 transition-colors">Applications</a> of conformal prediction in various fields, including bioinformatics, medicine, large language <a href="https://callforpaper.org/categories/models" title="Browse models call for papers" rel="follow" aria-label="View more models call for papers" class="!text-inherit !font-normal !underline decoration-dotted decoration-slate-400/60 underline-offset-4 cursor-pointer hover:decoration-slate-900 dark:hover:decoration-slate-100 transition-colors">models</a> and <a href="https://callforpaper.org/categories/information-1" title="Browse information call for papers" rel="follow" aria-label="View more information call for papers" class="!text-inherit !font-normal !underline decoration-dotted decoration-slate-400/60 underline-offset-4 cursor-pointer hover:decoration-slate-900 dark:hover:decoration-slate-100 transition-colors">information</a> <a href="https://callforpaper.org/categories/security-1" title="Browse security call for papers" rel="follow" aria-label="View more security call for papers" class="!text-inherit !font-normal !underline decoration-dotted decoration-slate-400/60 underline-offset-4 cursor-pointer hover:decoration-slate-900 dark:hover:decoration-slate-100 transition-colors">security</a>.<br>- <a href="https://callforpaper.org/categories/software-1" title="Browse Software call for papers" rel="follow" aria-label="View more Software call for papers" class="!text-inherit !font-normal !underline decoration-dotted decoration-slate-400/60 underline-offset-4 cursor-pointer hover:decoration-slate-900 dark:hover:decoration-slate-100 transition-colors">Software</a> implementations of conformal and probabilistic prediction frameworks and methods.<br>- Novel conformity measures.<br>- Distribution-free uncertainty quantification.<br>- Conformal <a href="https://callforpaper.org/categories/anomaly-detection" title="Browse anomaly detection call for papers" rel="follow" aria-label="View more anomaly detection call for papers" class="!text-inherit !font-normal !underline decoration-dotted decoration-slate-400/60 underline-offset-4 cursor-pointer hover:decoration-slate-900 dark:hover:decoration-slate-100 transition-colors">anomaly detection</a>.<br>- Conformal martingale <a href="https://callforpaper.org/categories/testing-1" title="Browse testing call for papers" rel="follow" aria-label="View more testing call for papers" class="!text-inherit !font-normal !underline decoration-dotted decoration-slate-400/60 underline-offset-4 cursor-pointer hover:decoration-slate-900 dark:hover:decoration-slate-100 transition-colors">testing</a> and change-point detection.<br>- Venn prediction and other methods of multi-probability prediction.<br>- Distributional prediction and conformal predictive distributions.<br>- Algorithmic <a href="https://callforpaper.org/categories/theory-1" title="Browse theory call for papers" rel="follow" aria-label="View more theory call for papers" class="!text-inherit !font-normal !underline decoration-dotted decoration-slate-400/60 underline-offset-4 cursor-pointer hover:decoration-slate-900 dark:hover:decoration-slate-100 transition-colors">theory</a> of randomness.<br>- Conformal prediction for explainability, causality and fairness, accountability and transparency (FAT).<br>- Probabilistic prediction.<br>- On-line <a href="https://callforpaper.org/categories/compression" title="Browse compression call for papers" rel="follow" aria-label="View more compression call for papers" class="!text-inherit !font-normal !underline decoration-dotted decoration-slate-400/60 underline-offset-4 cursor-pointer hover:decoration-slate-900 dark:hover:decoration-slate-100 transition-colors">compression</a> modelling.<br><br>The committee is open to consider any other recent and cutting edge development related to Conformal and Probabilistic Prediction.<br><br>All accepted papers will be presented at the conference and published in the PMLR (Proceedings of <a href="https://callforpaper.org/categories/machine-learning-3" title="Browse Machine Learning call for papers" rel="follow" aria-label="View more Machine Learning call for papers" class="!text-inherit !font-normal !underline decoration-dotted decoration-slate-400/60 underline-offset-4 cursor-pointer hover:decoration-slate-900 dark:hover:decoration-slate-100 transition-colors">Machine Learning</a> Research). Good papers will be invited to submit an extended version in a journal special issue.
	

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## 🏷 Taxonomy &amp; Topics
- **Primary Category**: N/A
- **Research Fields**: 
  - Artificial Intelligence
  - Uncategorized
  - Multidisciplinary &amp; General

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## 🧭 Agent Instructions
- **Standard Link**: `https://callforpaper.org/cfp/copa-2025-14th-symposium-on-conformal-and-probabilistic-prediction-with-applications_2486`
- **Markdown Link**: `https://callforpaper.org/cfp/copa-2025-14th-symposium-on-conformal-and-probabilistic-prediction-with-applications_2486.md`
- **PDF Version**: `https://callforpaper.org/cfp/copa-2025-14th-symposium-on-conformal-and-probabilistic-prediction-with-applications_2486.pdf`



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## 🎓 Academic Citations &amp; Bibliographic Records

Use these pre-formatted snippets to cite this Call for Papers in publications or reference managers:

### Plain Text
```text
COPA 2025 : 14th Symposium on Conformal and Probabilistic Prediction with Applications. September 10–12, 2025. Available at: https://callforpaper.org/cfp/copa-2025-14th-symposium-on-conformal-and-probabilistic-prediction-with-applications_2486. Accessed: July 21, 2026.
```

### APA Style 7th edition
```text
COPA 2025 : 14th Symposium on Conformal and Probabilistic Prediction with Applications. (2025, September 10–12). https://callforpaper.org/cfp/copa-2025-14th-symposium-on-conformal-and-probabilistic-prediction-with-applications_2486
```

### IEEE
```text
&quot;COPA 2025 : 14th Symposium on Conformal and Probabilistic Prediction with Applications,&quot; Sep. 10–12, 2025. [Online]. Available: https://callforpaper.org/cfp/copa-2025-14th-symposium-on-conformal-and-probabilistic-prediction-with-applications_2486. [Accessed: July 21, 2026].
```

### BibTeX
```bibtex
@misc{copa20252025cfp,
  title     = {COPA 2025 : 14th Symposium on Conformal and Probabilistic Prediction with Applications},
  year      = {2025},
  month     = sep,
  url       = {https://callforpaper.org/cfp/copa-2025-14th-symposium-on-conformal-and-probabilistic-prediction-with-applications_2486},
  note      = {Call for Papers. Accessed: 2026-07-21}
}
```

### RIS (Reference Manager, EndNote)
```ris
TY  - CONF
TI  - COPA 2025 : 14th Symposium on Conformal and Probabilistic Prediction with Applications
PY  - 2025
DA  - 2025/09/10
UR  - https://callforpaper.org/cfp/copa-2025-14th-symposium-on-conformal-and-probabilistic-prediction-with-applications_2486
N1  - Call for Papers. Accessed: 2026-07-21
ER  -
```

