4 citations · 5 across the 3 of their papers we have counts for
3 papers
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…
cs.LG2021★ 1 cited
An Operator Theoretic Approach for Analyzing Sequence Neural Networks
Ilan Naiman, Omri Azencot
Analyzing the inner mechanisms of deep neural networks is a fundamental task in machine learning. Existing work provides limited analysis or it depends on local theories, such as f…