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Constrained Learning for Scientific Modelling session announced for NeurIPS Paris pre-event

By PulseAugur Editorial · [1 sources] ·

A call for contributions has been issued for a session on Constrained Learning for Scientific Modelling (CL4SM) at an ELLI's UnConference, which serves as a pre-event for NeurIPS Paris. The session aims to foster discussions on machine learning models that incorporate prior knowledge such as conservation laws, symmetries, and boundary conditions, to ensure physical correctness in scientific and engineering applications. Submissions are invited for ongoing work and tutorials, with a deadline of October 30, 2026, and the session itself scheduled for December 8, 2026. AI

IMPACT This session aims to advance the development of physically accurate machine learning models for scientific applications.

RANK_REASON The item is a call for contributions to a workshop/session at an academic conference, focusing on a specific research area. [lever_c_demoted from research: ic=1 ai=1.0]

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AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

Constrained Learning for Scientific Modelling session announced for NeurIPS Paris pre-event

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The item is a call for contributions to a workshop/session at an academic conference, focusing on a specific research area. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. r/MachineLearning TIER_1 English(EN) · /u/cici118 ·

    Constrained Learning for Scientific Modelling (Paris NeurIPS pre-event) [N]

    <!-- SC_OFF --><div class="md"><p>CALL FOR CONTRIBUTIONS </p> <p>CL4SM session at ELLIs UnConference, a NeurIPS Paris pre-event: <a href="https://badulion.github.io/cl4sm%5C_2026/">https://badulion.github.io/cl4sm\_2026/</a></p> <p>Machine learning models of scientific and engine…

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