RESEARCH

Luo, Z., Sang, H. and Mallick, B. (2024) ``A Nonstationary soft partitioned Gaussian process model via random spanning trees'', Journal of the American Statistical Association, 119,2105-2116.

Niu, Y., Ni, Y., Pati, D. and Mallick, B. (2024) ``Covariate-Assisted Bayesian Graph Learning for Heterogeneous Data'', Journal of the American Statistical Association, 119,1985-1999.

Chakrabarti, A., Ni, Y., Morris, E., Salinas, M., Chapkin, R., Mallick, B. (2024) ``Graphical Dirichlet Process for Clustering Non-Exchangeable Grouped Data ", Journal of Machine Learning Research, 25, 1-56.

Lee, S., Zhao, P., Pati, D., Mallick, B. (2024) ``Tail-adaptive Bayesian shrinkage'', Electronic Journal of Statistics, To Appear.

 Das, S., Niu, Y., Ni, Y., Mallick, B., Pati, D. (2024) ``Blocked Gibbs  sampler for hierarchical Dirichlet Process' ', Journal of Computational and Graphical Statistics, To Appear.

 Zhao, P., Bhattacharya, A., Pati, D., Mallick, B. (2024)``Structured Optimal Variational Inference for Dynamic Latent Space Models'',  Journal of Machine Learning Research, 25, 1-55.

 Chakrabarti, A., Ni, Y and Mallick, B. (2024) ``Joint Bayesian estimation of cell dependence and gene associations in spatially resolved transcriptomic data'' Scientific Report, 14, 9516, https://doi.org/10.1038/s41598-024-60002-z.

Lei, B., Xu, D., Zhang, R and Mallick, B. (2024) ``Embracing Unknown Step by Step: Towards Reliable Sparse Training in Real World'', Transactions on Machine Learning Research, To Appear. 

 Helwig, J., Dasgupta, S., Zhai, P., Mallick, B. and Debdeep, D. (2024) ``A Covariate-Dependent Approach to Gaussian Graphical Modeling in R'', Transactions on Mathematical Software.

 Lei, B, Mahajan, A. and Mallick, B. (2024) ``Identifying and overcoming COVID-19 vaccination impediments using Bayesian data mining techniques'', Scientific Report, 14,8595, https://doi.org/10.1038/s41598-024-58902-1.

Payne, R., Guha, N. and Mallick, B. (2024) ``A Bayesian Survival Treed Hazards Model Using Latent Gaussian Processes'', Biometrics, To Appear.

Lei, B., Xu, D., Zhang, R., He, S., Mallick, B. (2024) ``Balance is Essence: Accelerating sparse training via adaptive gradient correction'', Conference on parsimony and learning (CPAL).

Mohseni, P., Duffield, N., Mallick, B. and Hasanzadeh (2023) ``Adaptive Conditional Quantile Neural Processes'', The Conference on Uncertainty in Artificial Intelligence (UAI), To appear.

Lee, K., Zhao, P., Bhattacharya, A., Mallick, B. and Xie, L. (2023) ``An Active Learning-based Approach for Hosting Capacity Analysis in Distribution Systems'',  IEEE Transactions on Smart Grid, To appear.

Lei, B., Xu, D., Zhang, R., Mallick, B. (2023) ``Calibrating the Rigged Lottery: Making All Tickets Reliable'', International Conference on Learning Representations (ICLR).

Luo, Z, Sang, H and Mallick, B. (2022) ``BAMDT: Bayesian additive semi-multivariate Trees for nonparametric regression'', International Conference on Machine Learning (ICML), 14509-14526.

Lei, B., Xu, D., Zhang, R., Mallick, B. (2022) ``Accelerating and Stabilizing Sparse Training'' .  Artificial Intelligence and Statistics (AISTAT). 

Lei, B., Xu, D., Zhang, R., Mallick, B. (2022) ``Reliable and Efficient Out-of-distribution Detection'',  International Conference on Learning Representations (ICLR).

 Ni, Y and Mallick (2022) ``Ordinal causal discovery'', Proceedings of machine Learning Research (PMLR), 180, 1530-1540.

 Ghosh, R. P., Maity, A. K., Pourahmadi, M., & Mallick, B. K. (2022) ``Adaptive Bayesian variable clustering via structural learning of breast cancer data'', Genetic Epidemiology, 47(1), 95-104.

  Lee, S. Y., & Mallick, B. K. (2022) ``Bayesian Hierarchical Modeling: Application Towards Production Results in the Eagle Ford Shale of South Texas'', Sankhya B, 84(1), 1-43.

Luo, Z., Sang H., Mallick B (2021) ``BAST: Bayesian Additive Regression spanning Tree for complex constrained domain'', 35th Conference on Neural Information Processing Systems(NeurIPS 2021)

Ghosh, R., Mallick, B. and Pourahmadi, M. (2021) ``Bayesian Estimation of C orrelation Matrices of Longitudinal Data'', Bayesian Analysis , 16(3), 1039-1058

Lei, B., Kirk, T., Bhattacharya, A., Pati, D., Qian, X., Arroyave, R. and Mallick, B. (2021)`` Bayesian optimization with adaptive surrogate models for automated eperimental design'', Nature Computational Materials, 7, 194,https://doi.org/10.1038/s41524-021-00662-x

Maity, A., Lee, SC, Hu, L, Bell-Pederson, D., Mallick, B. and Roy Sarkar, T. (2021) ``Circadian gene selection for time-to-event phenotype by integrating CNV and RNAseq data'', Chemometrics and Intelligent Laboratory Systems , 212, 104276. PMC8775911

Luo, Z., Sang, H. and Mallick, B. (2021)`` A Bayesian contiguous partitioning method for learning clustered latent variables'', Journal of Machine Learning Research, 22, 1-52

Sarkar, A., Pati, D., Mallick, B. and carroll, R. (2021) ``Bayesian Copula Density Deconvolution for Zero- Inflated Data in Nutritional Epidemiology'', Journal of the American Statistical Association , 116, 535, 1075-1087. PMC8654344

Niu, Y., Pati, D., Mallick, B. (2021) ``Bayesian Graph selection consistency under Model Misspecification", Bernoulli , 27(1), 637-672. PMC8300537

Geng, Xinbo, Lang Tong, Anirban Bhattacharya, Bani Mallick, and Le Xie. "Probabilistic hosting capacity analysis via bayesian optimization." In 2021 IEEE Power & Energy Society General Meeting (PESGM) , pp. 1-5. IEEE, 2021