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Timothy L. Molloy

16 papers hereh-index 16700 citations64 works total

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

author position
  • sole author1
  • first author8
  • middle author2
  • last author5

Across the 16 of 16 papers where every author was matched, so the position is known.

fields
  • eess.SY12
  • cs.CV2
  • cs.RO1
  • math.OC1
same name
  • Timothy L. Molloy — 8 papers, h 2
  • Timothy L. Molloy — 3 papers, h 2
  • Timothy L. Molloy — 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
20182023
most citedAsynchronous Blob Tracker for Event Cameras

20 citations · 39 across the 10 of their papers we have counts for

collaborators
Showing 2021Show all

4 papers · 1 filter

eess.SY2021★ 6 cited

Entropy-Regularized Partially Observed Markov Decision Processes

Timothy L. Molloy, Girish N. Nair

We investigate partially observed Markov decision processes (POMDPs) with cost functions regularized by entropy terms describing state, observation, and control uncertainty. Standa…

eess.SY2021★ 13 cited

Smoother Entropy for Active State Trajectory Estimation and Obfuscation in POMDPs

Timothy L. Molloy, Girish N. Nair

We study the problem of controlling a partially observed Markov decision process (POMDP) to either aid or hinder the estimation of its state trajectory. We encode the estimation ob…

eess.SY2021

Active Trajectory Estimation for Partially Observed Markov Decision Processes via Conditional Entropy

Timothy L. Molloy, Girish N. Nair

In this paper, we consider the problem of controlling a partially observed Markov decision process (POMDP) in order to actively estimate its state trajectory over a fixed horizon w…

eess.SY2021

Smoothing-Averse Control: Covertness and Privacy from Smoothers

Timothy L. Molloy, Girish N. Nair

In this paper we investigate the problem of controlling a partially observed stochastic dynamical system such that its state is difficult to infer using a (fixed-interval) Bayesian…

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