A Scalable Training-Free Diffusion Model for Uncertainty Quantification

Generative artificial intelligence extends beyond its success in image/text synthesis, proving itself a powerful uncertainty quantification (UQ) technique through its capability to sample from complex high-dimensional probability distributions. However, existing methods often require a complicated t...

Celý popis

Podrobná bibliografia

Vydané v:	SC24-W: Workshops of the International Conference for High Performance Computing, Networking, Storage and Analysis s. 380 - 386
Hlavní autori:	Muhammad Rafid, Ali Haisam, Yin, Junqi, Geng, Yuwei, Liang, Siming, Bao, Feng, Ju, Lili, Zhang, Guannan
Médium:	Konferenčný príspevok..
Jazyk:	English
Vydavateľské údaje:	IEEE 17.11.2024
Predmet:	Adaptation models Diffusion models Hurricanes Load modeling Probability distribution Scalability Stochastic processes Supercomputers Training Uncertainty
On-line prístup:	Získať plný text
Tagy:	Pridať tag Žiadne tagy, Buďte prvý, kto otaguje tento záznam!