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Jamming transition as a paradigm to understand the loss landscape of deep neural networks

Research article (Physical review. E, 2019) · cited 123× · AI/ML
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Jamming transition as a paradigm to understand the loss landscape of deep neural networks

Summary

Jamming transition as a paradigm to understand the loss landscape of deep neural networks is a scholarly article[1].

Key Facts

  • Jamming transition as a paradigm to understand the loss landscape of deep neural networks's instance of is recorded as scholarly article[2].

Related Entities

Levent Sagun

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Direct Wikidata claims

  1. [2] ↑ . wikidata.org.

Class ancestry

  1. [1] ↑ . Wikidata. wikidata.org.

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APA 4ort.xyz Knowledge Graph. (2026). Jamming transition as a paradigm to understand the loss landscape of deep neural networks. Retrieved May 24, 2026, from https://4ort.xyz/entity/jamming-transition-as-a-paradigm-to-understand-the-loss-landscape-of-deep-neural-networks
MLA “Jamming transition as a paradigm to understand the loss landscape of deep neural networks.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/jamming-transition-as-a-paradigm-to-understand-the-loss-landscape-of-deep-neural-networks.
BibTeX @misc{4ortxyz_jamming-transition-as-a-paradigm-to-understand-the-loss-landscape-of-deep-neural-networks_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Jamming transition as a paradigm to understand the loss landscape of deep neural networks}}, year = {2026}, url = {https://4ort.xyz/entity/jamming-transition-as-a-paradigm-to-understand-the-loss-landscape-of-deep-neural-networks}, note = {Accessed: 2026-05-24}}
LLM prompt According to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): Jamming transition as a paradigm to understand the loss landscape of deep neural networks — https://4ort.xyz/entity/jamming-transition-as-a-paradigm-to-understand-the-loss-landscape-of-deep-neural-networks (retrieved 2026-05-24)

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