4 citations · 7 across the 3 of their papers we have counts for
3 papers
physics.geo-ph2024★ 3 cited
Learning Physics for Unveiling Hidden Earthquake Ground Motions via Conditional Generative Modeling
Pu Ren, Rie Nakata, Maxime Lacour +9
Predicting high-fidelity ground motions for future earthquakes is crucial for seismic hazard assessment and infrastructure resilience. Conventional empirical simulations suffer fro…
cs.LG2023
Sample and Predict Your Latent: Modality-free Sequential Disentanglement via Contrastive Estimation
Ilan Naiman, Nimrod Berman, Omri Azencot
Unsupervised disentanglement is a long-standing challenge in representation learning. Recently, self-supervised techniques achieved impressive results in the sequential setting, wh…
cs.LG2023★ 4 cited
Multifactor Sequential Disentanglement via Structured Koopman Autoencoders
Nimrod Berman, Ilan Naiman, Omri Azencot
Disentangling complex data to its latent factors of variation is a fundamental task in representation learning. Existing work on sequential disentanglement mostly provides two fact…