Mixture Manifold Networks: A Computationally Efficient Baseline for Inverse Modeling
Publication
, Preprint
Spell, GP; Ren, S; Collins, LM; Malof, JM
November 25, 2022
Duke Scholars
Publication Date
November 25, 2022
Citation
APA
Chicago
ICMJE
MLA
NLM
Spell, G. P., Ren, S., Collins, L. M., & Malof, J. M. (2022). Mixture Manifold Networks: A Computationally Efficient Baseline for
Inverse Modeling.
Spell, Gregory P., Simiao Ren, Leslie M. Collins, and Jordan M. Malof. “Mixture Manifold Networks: A Computationally Efficient Baseline for
Inverse Modeling,” November 25, 2022.
Spell GP, Ren S, Collins LM, Malof JM. Mixture Manifold Networks: A Computationally Efficient Baseline for
Inverse Modeling. 2022.
Spell, Gregory P., et al. Mixture Manifold Networks: A Computationally Efficient Baseline for
Inverse Modeling. 25 Nov. 2022.
Spell GP, Ren S, Collins LM, Malof JM. Mixture Manifold Networks: A Computationally Efficient Baseline for
Inverse Modeling. 2022.
Publication Date
November 25, 2022