Preprints & working papers

Markovian and non-markovian processes with active decision making strategies for addressing the COVID-19 pandemic. Eftekhari, H., Mukherjee, D., Banerjee, M., and Ritov, Y. arXiv preprint arXiv:2008.00375, 2020.

Utopia: Universally trainable optimal prediction intervals aggregation. Fan, J., Ge, J., and Mukherjee, D. arXiv preprint arXiv:2306.16549, 2023.

Trade-off between dependence and complexity for nonparametric learning–an empirical process approach. Deb, N. and Mukherjee, D. arXiv preprint arXiv:2401.08978, 2024.

Optimal aggregation of prediction intervals under unsupervised domain shift. Ge, J., Mukherjee, D., and Fan, J. Advances in Neural Information Processing Systems, 2024, 73605–73637.

Transfer learning under high-dimensional graph convolutional regression model for node classification. Chen, J., Huang, D., Wang, L., Lunetta, K. L., Mukherjee, D., and Cheng, H. arXiv preprint arXiv:2405.16672, 2024.

On the estimation rate of bayesian PINN for inverse problems. Sun, Y., Mukherjee, D., and Atchade, Y. arXiv preprint arXiv:2406.14808, 2024.

A debiased estimator for the mediation functional in ultra-high-dimensional setting in the presence of interaction effects. Bo, S., Ghassami, A., and Mukherjee, D. arXiv preprint arXiv:2412.08827, 2024.

Estimation and inference for the average treatment effect in a score-explained heterogeneous treatment effect model. Wibisono, K. C., Mukherjee, D., Banerjee, M., and Ritov, Y. arXiv preprint arXiv:2504.17126, 2025.

Transfer learning under high-dimensional network convolutional regression model. Wang, L., Chen, J., Lunetta, K. L., Huang, D., Cheng, H., and Mukherjee, D. arXiv preprint arXiv:2504.19979, 2025.

DRO-augment framework: Robustness by synergizing wasserstein distributionally robust optimization and data augmentation. Hu, J., Mukherjee, D., and Paschalidis, I. C. arXiv preprint arXiv:2506.17874, 2025.

Phase transition in nonparametric minimax rates for covariate shifts on approximate manifolds. Wang, Y., Deb, N., and Mukherjee, D. arXiv preprint arXiv:2507.00889, 2025.

CCFC: Core & core-full-core dual-track defense for LLM jailbreak protection. Hu, J., Wang, H., Mukherjee, D., and Paschalidis, I. C. arXiv preprint arXiv:2508.14128, 2025.

CINDES: Classification induced neural density estimator and simulator. Dai, D., Fan, J., Gu, Y., and Mukherjee, D. arXiv preprint arXiv:2510.00367, 2025.