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Prashant Singh

8 papers hereh-index 12371 citations26 works total

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

author position
  • sole author1
  • first author5
  • middle author1
  • last author1

Across the 8 of 8 papers where every author was matched, so the position is known.

fields
  • cond-mat.stat-mech5
  • stat.ML3
same name
  • Prashant Singh — 6 papers, h 3
  • Prashant Singh — 5 papers, h 4
  • Prashant Singh — 4 papers
  • Prashant Singh — 4 papers, h 7
  • Prashant Singh — 3 papers
  • Prashant Singh — 3 papers

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
20182021
most citedRandom acceleration process under stochastic resetting

49 citations · 99 across the 3 of their papers we have counts for

collaborators
Showing 2020Show all

4 papers · 1 filter

cond-mat.stat-mech2020★ 24 cited

Local time for run and tumble particle

Prashant Singh, Anupam Kundu

We investigate the local time (Tloc​) statistics for a run and tumble particle in an one dimensional inhomogeneous medium. The inhomogeneity is introduced by considering the po…

cond-mat.stat-mech2020★ 49 cited

Random acceleration process under stochastic resetting

Prashant Singh

We consider the motion of a randomly accelerated particle in one dimension under stochastic resetting mechanism. Denoting the position and velocity by x and v respectively, we…

cond-mat.stat-mech2020★ 26 cited

Run-and-Tumble particle in inhomogeneous media in one dimension

Prashant Singh, Sanjib Sabhapandit, Anupam Kundu

We investigate the run and tumble particle (RTP), also known as persistent Brownian motion, in one dimension. A telegraphic noise σ(t) drives the particle which changes between $…

stat.ML2020

Convolutional Neural Networks as Summary Statistics for Approximate Bayesian Computation

Mattias Åkesson, Prashant Singh, Fredrik Wrede +1

Approximate Bayesian Computation is widely used in systems biology for inferring parameters in stochastic gene regulatory network models. Its performance hinges critically on the a…

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