activity
20172022
most citedConic Scan-and-Cover algorithms for nonparametric topic modeling

6 citations · 9 across the 6 of their papers we have counts for

collaborators

8 papers

stat.AP20221 cited

Towards Algorithmic Fairness in Space-Time: Filling in Black Holes

Cheryl Flynn, Aritra Guha, Subhabrata Majumdar +2

New technologies and the availability of geospatial data have drawn attention to spatio-temporal biases present in society. For example: the COVID-19 pandemic highlighted dispariti…

stat.ML2021

Scalable nonparametric Bayesian learning for heterogeneous and dynamic velocity fields

Sunrit Chakraborty, Aritra Guha, Rayleigh Lei +1

Analysis of heterogeneous patterns in complex spatio-temporal data finds usage across various domains in applied science and engineering, including training autonomous vehicles to…

stat.ME2020

Outlier-Robust Optimal Transport

Debarghya Mukherjee, Aritra Guha, Justin Solomon +2

Optimal transport (OT) measures distances between distributions in a way that depends on the geometry of the sample space. In light of recent advances in computational OT, OT dista…

cs.LG2020

Robust Unsupervised Learning of Temporal Dynamic Interactions

Aritra Guha, Rayleigh Lei, Jiacheng Zhu +2

Robust representation learning of temporal dynamic interactions is an important problem in robotic learning in general and automated unsupervised learning in particular. Temporal d…

stat.ML20191 cited

Dirichlet Simplex Nest and Geometric Inference

Mikhail Yurochkin, Aritra Guha, Yuekai Sun +1

We propose Dirichlet Simplex Nest, a class of probabilistic models suitable for a variety of data types, and develop fast and provably accurate inference algorithms by accounting f…

math.ST20191 cited

On posterior contraction of parameters and interpretability in Bayesian mixture modeling

Aritra Guha, Nhat Ho, XuanLong Nguyen

We study posterior contraction behaviors for parameters of interest in the context of Bayesian mixture modeling, where the number of mixing components is unknown while the model it…