---
title: Optimizing Workflows with Neural Networks
url: https://www.ml-quant.com/papers/ssrn/5195894/
site: ML-Quant (https://www.ml-quant.com)
updated: 2026-09-26
license: Summaries CC BY 4.0; links go to the original sources
index: https://www.ml-quant.com/llms.txt
identifier: SSRN 5195894
source_url: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=5195894
featured: 2025-04-02
citations: unknown
topic: ML & AI Methods
---


# Optimizing Workflows with Neural Networks

The article discusses a hybrid approach to optimizing work processes by transferring some tasks to neural networks and solving the rest using alternative methods, leading to reduced energy costs and improved efficiency.

- Source: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=5195894
- Identifier: SSRN 5195894
- Released: 2025-03-27
- First featured: Quant Letter No. 91 (2025-04-02): https://www.ml-quant.com/issues/2025-04-02/
- Citations (Semantic Scholar): not tracked
- Published in: not yet
- Topic: ML & AI Methods

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