most citedMulti-modal data generation with a deep metric variational autoencoder

3 citations

researchers with a paper here

Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.

collaborating institutions

2 papers

cs.SD2025★ 1 cited

In situ estimation of the acoustic surface impedance using simulation-based inference

Jonas M. Schmid, Johannes D. Schmid, Martin Eser +1

Accurate acoustic simulations of enclosed spaces require precise boundary conditions, typically expressed through surface impedances for wave-based methods. Conventional measuremen…

eess.IV2022★ 3 cited

Multi-modal data generation with a deep metric variational autoencoder

Josefine Vilsbøll Sundgaard, Morten Rieger Hannemose, Søren Laugesen +6

We present a deep metric variational autoencoder for multi-modal data generation. The variational autoencoder employs triplet loss in the latent space, which allows for conditional…