most citedMultiple testing in multi-stream sequential change detection

1 citations · 1 across the 3 of their papers we have counts for

collaborators

5 papers

stat.AP2026

Downscaling land surface temperature data using edge detection and block-diagonal Gaussian process regression

Sanjit Dandapanthula, Margaret Johnson, Madeleine Pascolini-Campbell +2

Accurate and high-resolution estimation of land surface temperature (LST) is crucial in estimating evapotranspiration, a measure of plant water use and a central quantity in agricu…

cs.LG2025

Optimal Transportation and Alignment Between Gaussian Measures

Sanjit Dandapanthula, Aleksandr Podkopaev, Shiva Prasad Kasiviswanathan +2

Optimal transport (OT) and Gromov-Wasserstein (GW) alignment provide interpretable geometric frameworks for comparing, transforming, and aggregating heterogeneous datasets -- tasks…

cs.LG2025

Gradient descent for deep equilibrium single-index models

Sanjit Dandapanthula, Aaditya Ramdas

Deep equilibrium models (DEQs) have recently emerged as a powerful paradigm for training infinitely deep weight-tied neural networks that achieve state of the art performance acros…

math.ST20251 cited

Multiple testing in multi-stream sequential change detection

Sanjit Dandapanthula, Aaditya Ramdas

Multi-stream sequential change detection involves simultaneously monitoring many streams of data and trying to detect when their distributions change, if at all. Here, we theoretic…

stat.ME2025

Anytime-valid FDR control with the stopped e-BH procedure

Hongjian Wang, Sanjit Dandapanthula, Aaditya Ramdas

The recent e-Benjamini-Hochberg (e-BH) procedure for multiple hypothesis testing is known to control the false discovery rate (FDR) under arbitrary dependence between the input e-v…