Statistical Regeneration Guarantees of the Wasserstein Autoencoder with Latent Space Consistency. - Anish Chakrabarty; Swagatam Das (NeurIPS, 2021)

On Translation and Reconstruction Guarantees of the Cycle-Consistent Generative Adversarial Networks. - Anish Chakrabarty; Swagatam Das (NeurIPS, 2022)

Interval Bound Interpolation for Few-shot Learning with Few Tasks. - Shounak Datta; Sankha Subhra Mullick; Anish Chakrabarty; Swagatam Das (ICML, 2023)

Concurrent Density Estimation with Wasserstein Autoencoders: Some Statistical Insights. - Anish Chakrabarty; Arkaprabha Basu; Swagatam Das (CoRR, 2023)

Lost in Translation: GANs' Inability to Generate Simple Probability Distributions. - Debanjan Dutta; Anish Chakrabarty; Swagatam Das (Tiny Papers @ ICLR, 2024)

Fortifying Fully Convolutional Generative Adversarial Networks for Image Super-Resolution Using Divergence Measures. - Arkaprabha Basu; Kushal Bose; Sankha Subhra Mullick; Anish Chakrabarty; Swagatam Das (CoRR, 2024)

On Robust Cross Domain Alignment. - Anish Chakrabarty; Arkaprabha Basu; Swagatam Das (CoRR, 2024)

Enhancing Contrastive Clustering with Negative Pair-guided Regularization. - Abhishek Kumar 010; Anish Chakrabarty; Sankha Subhra Mullick; Swagatam Das (Trans. Mach. Learn. Res., 2024)

On the Existence of Universal Simulators of Attention. - Debanjan Dutta; Faizanuddin Ansari; Anish Chakrabarty; Swagatam Das (CoRR, 2025)

Relation-Aware Slicing in Cross-Domain Alignment. - Dhruv Sarkar; Aprameyo Chakrabartty; Anish Chakrabarty; Swagatam Das (CoRR, 2025)

Information preservation with wasserstein autoencoders: generation consistency and adversarial robustness. - Anish Chakrabarty; Arkaprabha Basu; Swagatam Das (Stat. Comput., 2025)