| Statistical Regeneration Guarantees of the Wasserstein Autoencoder with Latent Space Consistency A Chakrabarty, S Das Advances in Neural Information Processing Systems 35, 2021 | 8 | 2021 |
| On strong consistency of kernel k-means: A Rademacher complexity approach A Chakrabarty, S Das Statistics & Probability Letters 182, 109291, 2022 | 5 | 2022 |
| Interval bound interpolation for few-shot learning with few tasks S Datta, SS Mullick, A Chakrabarty, S Das International Conference on Machine Learning, 7141-7166, 2023 | 2 | 2023 |
| On Translation and Reconstruction Guarantees of the Cycle-Consistent Generative Adversarial Networks A Chakrabarty, S Das Advances in Neural Information Processing Systems 36, 2022 | 1 | 2022 |
| Fortifying Fully Convolutional Generative Adversarial Networks for Image Super-Resolution Using Divergence Measures A Basu, K Bose, SS Mullick, A Chakrabarty, S Das arXiv preprint arXiv:2404.06294, 2024 | | 2024 |
| Concurrent Density Estimation with Wasserstein Autoencoders: Some Statistical Insights A Chakrabarty, A Basu, S Das arXiv preprint arXiv:2312.06591, 2023 | | 2023 |
| Lost in Translation: GANs' Inability to Generate Simple Probability Distributions D Dutta, A Chakrabarty, S Das The Second Tiny Papers Track at ICLR 2024, 0 | | |
Swagatam DasProfessor, Electronics and Communication Sciences Unit, Indian Statistical Institute, KolkataDirección de correo verificada de isical.ac.in
