Modern AI versus century-old mathematical models: How far can we go with generative adversarial networks to reproduce stochastic processes?

Research article (Physica D Nonlinear Phenomena, 2023) · cited 11× · AI/ML
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Modern AI versus century-old mathematical models: How far can we go with generative adversarial networks to reproduce stochastic processes?

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APA 4ort.xyz Knowledge Graph. (2026). Modern AI versus century-old mathematical models: How far can we go with generative adversarial networks to reproduce stochastic processes?. Retrieved May 24, 2026, from https://4ort.xyz/entity/modern-ai-versus-century-old-mathematical-models-how-far-can-we-go-with-generative-adversarial-networks-to-reproduce-sto
MLA “Modern AI versus century-old mathematical models: How far can we go with generative adversarial networks to reproduce stochastic processes?.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/modern-ai-versus-century-old-mathematical-models-how-far-can-we-go-with-generative-adversarial-networks-to-reproduce-sto.
BibTeX @misc{4ortxyz_modern-ai-versus-century-old-mathematical-models-how-far-can-we-go-with-generative-adversarial-networks-to-reproduce-sto_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Modern AI versus century-old mathematical models: How far can we go with generative adversarial networks to reproduce stochastic processes?}}, year = {2026}, url = {https://4ort.xyz/entity/modern-ai-versus-century-old-mathematical-models-how-far-can-we-go-with-generative-adversarial-networks-to-reproduce-sto}, note = {Accessed: 2026-05-24}}
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