Anindya Bhadra

16 papers A* 1A 1Journal 11Unranked 3
YearRankTypeTitle / Venue / Authors
2025 A* conf
Deep Kernel Posterior Learning under Infinite Variance Prior Weights.
ICLR
Jorge Loría, Anindya Bhadra
2024 J jnl
Deep Kernel Posterior Learning under Infinite Variance Prior Weights.
CoRR
Jorge Loría, Anindya Bhadra
2024 J jnl
Evidence Estimation in Gaussian Graphical Models Using a Telescoping Block Decomposition of the Precision Matrix.
J. Mach. Learn. Res.
Anindya Bhadra, Ksheera Sagar, David Rowe, Sayantan Banerjee, Jyotishka Datta
2024 A conf
Posterior Inference on Shallow Infinitely Wide Bayesian Neural Networks under Weights with Unbounded Variance.
UAI
Jorge Loría, Anindya Bhadra
2024 J jnl
SURE-tuned bridge regression.
Stat. Comput.
Jorge Loría, Anindya Bhadra
2023 — conf
Cluster Analysis to Find Temporal Physical Activity Patterns Among US Adults.
ICHI
Jiaqi Guo, Marah M. Aqeel, Luotao Lin, Saul B. Gelfand, Heather A. Eicher-Miller, Anindya Bhadra, Erin Hennessy, Elizabeth A. Richards, Edward J. Delp
2023 — conf
Joint Temporal Patterns By Integrating Diet and Physical Activity.
ICDH
Jiaqi Guo, Luotao Lin, Marah M. Aqeel, Saul B. Gelfand, Heather A. Eicher-Miller, Anindya Bhadra, Erin Hennessy, Elizabeth A. Richards, Edward J. Delp
2023 J jnl
Posterior Inference on Infinitely Wide Bayesian Neural Networks under Weights with Unbounded Variance.
CoRR
Jorge Loría, Anindya Bhadra
2022 J jnl
A Laplace Mixture Representation of the Horseshoe and Some Implications.
IEEE Signal Process. Lett.
Ksheera Sagar, Anindya Bhadra
2021 J jnl
Joint mean-covariance estimation via the horseshoe.
J. Multivar. Anal.
Yunfan Li, Jyotishka Datta, Bruce A. Craig, Anindya Bhadra
2021 J jnl
Merging Two Cultures: Deep and Statistical Learning.
CoRR
Anindya Bhadra, Jyotishka Datta, Nicholas G. Polson, Vadim Sokolov, Jianeng Xu
2019 J jnl
Prediction Risk for the Horseshoe Regression.
J. Mach. Learn. Res.
Anindya Bhadra, Jyotishka Datta, Yunfan Li, Nicholas G. Polson, Brandon T. Willard
2016 J jnl
Adaptive particle allocation in iterated sequential Monte Carlo via approximating meta-models.
Stat. Comput.
Anindya Bhadra, Edward L. Ionides
2016 J jnl
Exact sampling of the unobserved covariates in Bayesian spline models for measurement error problems.
Stat. Comput.
Anindya Bhadra, Raymond J. Carroll
2013 — conf
Integrative sparse Bayesian analysis of high-dimensional multi-platform genomic data in glioblastoma.
GENSiPS
Anindya Bhadra, Veerabhadran Baladandayuthapani
2010 J jnl
Forcing Versus Feedback: Epidemic Malaria and Monsoon Rains in Northwest India.
PLoS Comput. Biol.
Karina Laneri, Anindya Bhadra, Edward L. Ionides, Menno J. Bouma, Ramesh C. Dhiman, Rajpal S. Yadav, Mercedes Pascual