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researcher

Ritwik Sadhu

University of Washington

6 papers hereh-index 5151 citations9 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • first author3
  • middle author1
  • last author2

Across the 6 of 6 papers where every author was matched, so the position is known.

fields
  • math.ST4
  • math.PR1
  • stat.ML1
affiliations
  • University of Washington
  • Cornell University
  • Interdigital, Inc.
ORCID 0000-0003-0262-4012
same name
  • Ritwik Sadhu — 1 paper

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20212024
most citedStatistical inference with regularized optimal transport

8 citations · 23 across the 6 of their papers we have counts for

collaborators
Showing math.STShow all

4 papers · 1 filter

math.ST2023★ 3 cited

Stability and statistical inference for semidiscrete optimal transport maps

Ritwik Sadhu, Ziv Goldfeld, Kengo Kato

We study statistical inference for the optimal transport (OT) map (also known as the Brenier map) from a known absolutely continuous reference distribution onto an unknown finitely…

math.ST2022

Detecting Planted Partition in Sparse Multi-Layer Networks

Anirban Chatterjee, Sagnik Nandy, Ritwik Sadhu

Multilayer networks are used to represent the interdependence between the relational data of individuals interacting with each other via different types of relationships. To study…

math.ST2022★ 8 cited

Statistical inference with regularized optimal transport

Ziv Goldfeld, Kengo Kato, Gabriel Rioux +1

Optimal transport (OT) is a versatile framework for comparing probability measures, with many applications to statistics, machine learning, and applied mathematics. However, OT dis…

math.ST2021★ 8 cited

Limit Distribution Theory for the Smooth 1-Wasserstein Distance with Applications

Ritwik Sadhu, Ziv Goldfeld, Kengo Kato

The smooth 1-Wasserstein distance (SWD) W1σ​ was recently proposed as a means to mitigate the curse of dimensionality in empirical approximation while preserving the Wasserstein…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.