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Relation-Aware Slicing in Cross-Domain Alignment
Dhruv Sarkar, Aprameyo Chakrabartty, Anish Chakrabarty +1
The Sliced Gromov-Wasserstein (SGW) distance, aiming to relieve the computational cost of solving a non-convex quadratic program that is the Gromov-Wasserstein distance, utilizes p…
On Robust Cross Domain Alignment
Anish Chakrabarty, Arkaprabha Basu, Swagatam Das
The Gromov-Wasserstein (GW) distance is an effective measure of alignment between distributions supported on distinct ambient spaces. Calculating essentially the mutual departure f…
Concurrent Density Estimation with Wasserstein Autoencoders: Some Statistical Insights
Anish Chakrabarty, Arkaprabha Basu, Swagatam Das
Variational Autoencoders (VAEs) have been a pioneering force in the realm of deep generative models. Amongst its legions of progenies, Wasserstein Autoencoders (WAEs) stand out in…
Statistical Regeneration Guarantees of the Wasserstein Autoencoder with Latent Space Consistency
Anish Chakrabarty, Swagatam Das
The introduction of Variational Autoencoders (VAE) has been marked as a breakthrough in the history of representation learning models. Besides having several accolades of its own,…