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S. Sankaranarayanan

40 papers hereh-index 448.7k citations251 works total

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

author position
  • sole author1
  • first author1
  • middle author10
  • last author28

Across the 40 of 40 papers where every author was matched, so the position is known.

fields
  • math.OC13
  • eess.SY9
  • cs.RO5
  • cs.LG4
  • cs.GT2
  • cs.PL2
same name
  • S. Sankaranarayanan — 36 papers, h 51
  • S. Sankaranarayanan — 16 papers, h 19
  • S. Sankaranarayanan — 6 papers, h 8
  • S. Sankaranarayanan — 1 paper, h 1
  • S. Sankaranarayanan — 1 paper, h 2
  • S. Sankaranarayanan — 1 paper, h 13

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
20122024
most citedOutput Range Analysis for Deep Neural Networks

75 citations · 261 across the 31 of their papers we have counts for

collaborators
Showing 2017Show all

4 papers · 1 filter

eess.SY2017★ 4 cited

A Class of Control Certificates to Ensure Reach-While-Stay for Switched Systems

Hadi Ravanbakhsh, Sriram Sankaranarayanan

In this article, we consider the problem of synthesizing switching controllers for temporal properties through the composition of simple primitive reach-while-stay (RWS) properties…

cs.LG2017★ 75 cited

Output Range Analysis for Deep Neural Networks

Souradeep Dutta, Susmit Jha, Sriram Sanakaranarayanan +1

Deep neural networks (NN) are extensively used for machine learning tasks such as image classification, perception and control of autonomous systems. Increasingly, these deep NNs a…

eess.SY2017★ 20 cited

Learning Lyapunov (Potential) Functions from Counterexamples and Demonstrations

Hadi Ravanbakhsh, Sriram Sankaranarayanan

We present a technique for learning control Lyapunov (potential) functions, which are used in turn to synthesize controllers for nonlinear dynamical systems. The learning framework…

cs.PL2017★ 2 cited

Discriminating Traces with Time

Saeid Tizpaz-Niari, Pavol Cerny, Bor-Yuh Evan Chang +2

What properties about the internals of a program explain the possible differences in its overall running time for different inputs? In this paper, we propose a formal framework for…

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