Point-wise conditional diffusion models for physical systems with shape variations: Applications to spatio-temporal and large-scale systems.
- DOI
- 10.1016/j.neunet.2026.109186
- Published
- 2026 Nov
- Container
- Neural networks : the official journal of the International Neural Network Society
- Publisher
- Not recorded
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.1016/j.neunet.2026.109186,
title = {Point-wise conditional diffusion models for physical systems with shape variations: Applications to spatio-temporal and large-scale systems.},
author = {Kim J and Yang S and Kang N},
year = {2026},
journal = {Neural networks : the official journal of the International Neural Network Society},
doi = {10.1016/j.neunet.2026.109186},
url = {https://doi.org/10.1016/j.neunet.2026.109186}
}RIS
TY - JOUR TI - Point-wise conditional diffusion models for physical systems with shape variations: Applications to spatio-temporal and large-scale systems. AU - Kim J AU - Yang S AU - Kang N PY - 2026 JO - Neural networks : the official journal of the International Neural Network Society DO - 10.1016/j.neunet.2026.109186 UR - https://doi.org/10.1016/j.neunet.2026.109186 ER -
APA
J, K., S, Y., & N, K. (2026). Point-wise conditional diffusion models for physical systems with shape variations: Applications to spatio-temporal and large-scale systems.. Neural networks : the official journal of the International Neural Network Society. https://doi.org/10.1016/j.neunet.2026.109186
Source records
- pubmed · retrieved 2026-09-26T15:55:55.716Z