activity
20182021
most citedRecurrent Neural Networks for Fuzz Testing Web Browsers

10 citations · 11 across the 3 of their papers we have counts for

collaborators

5 papers

cs.LG2021

Learning Robust Controllers Via Probabilistic Model-Based Policy Search

Valentin Charvet, Bjørn Sand Jensen, Roderick Murray-Smith

Model-based Reinforcement Learning estimates the true environment through a world model in order to approximate the optimal policy. This family of algorithms usually benefits from…

cs.LG20201 cited

Odd-One-Out Representation Learning

Salman Mohammadi, Anders Kirk Uhrenholt, Bjørn Sand Jensen

The effective application of representation learning to real-world problems requires both techniques for learning useful representations, and also robust ways to evaluate propertie…

cs.RO2020

Intrinsic Robotic Introspection: Learning Internal States From Neuron Activations

Nikos Pitsillos, Ameya Pore, Bjorn Sand Jensen +1

We present an introspective framework inspired by the process of how humans perform introspection. Our working assumption is that neural network activations encode information, and…

cs.LG2020

Probabilistic selection of inducing points in sparse Gaussian processes

Anders Kirk Uhrenholt, Valentin Charvet, Bjørn Sand Jensen

Sparse Gaussian processes and various extensions thereof are enabled through inducing points, that simultaneously bottleneck the predictive capacity and act as the main contributor…

cs.CR201810 cited

Recurrent Neural Networks for Fuzz Testing Web Browsers

Martin Sablotny, Bjørn Sand Jensen, Chris W. Johnson

Generation-based fuzzing is a software testing approach which is able to discover different types of bugs and vulnerabilities in software. It is, however, known to be very time con…