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Diversified Flow Matching with Translation Identifiability
Sagar Shrestha, Xiao Fu
Diversified distribution matching (DDM) finds a unified translation function mapping a diverse collection of conditional source distributions to their target counterparts. DDM was…
Content-Style Learning from Unaligned Domains: Identifiability under Unknown Latent Dimensions
Sagar Shrestha, Xiao Fu
Understanding identifiability of latent content and style variables from unaligned multi-domain data is essential for tasks such as domain translation and data generation. Existing…
Identifiable Shared Component Analysis of Unpaired Multimodal Mixtures
Subash Timilsina, Sagar Shrestha, Xiao Fu
A core task in multi-modal learning is to integrate information from multiple feature spaces (e.g., text and audio), offering modality-invariant essential representations of data.…
Towards Identifiable Unsupervised Domain Translation: A Diversified Distribution Matching Approach
Sagar Shrestha, Xiao Fu
Unsupervised domain translation (UDT) aims to find functions that convert samples from one domain (e.g., sketches) to another domain (e.g., photos) without changing the high-level…
Communication-Efficient Federated Linear and Deep Generalized Canonical Correlation Analysis
Sagar Shrestha, Xiao Fu
Classic and deep generalized canonical correlation analysis (GCCA) algorithms seek low-dimensional common representations of data entities from multiple ``views'' (e.g., audio and…