275 citations · 341 across the 23 of their papers we have counts for
8 papers · 1 filter
Verification of deep probabilistic models
Krishnamurthy Dvijotham, Marta Garnelo, Alhussein Fawzi +1
Probabilistic models are a critical part of the modern deep learning toolbox - ranging from generative models (VAEs, GANs), sequence to sequence models used in machine translation…
A Sufficient Condition for Small-Signal Stability and Construction of Robust Stability Region
Parikshit Pareek, Konstantin Turitsyn, Krishnamurthy Dvijotham +1
The small-signal stability is an integral part of the power system security analysis. The introduction of renewable source related uncertainties is making the stability assessment…
On the Effectiveness of Interval Bound Propagation for Training Verifiably Robust Models
Sven Gowal, Krishnamurthy Dvijotham, Robert Stanforth +6
Recent work has shown that it is possible to train deep neural networks that are provably robust to norm-bounded adversarial perturbations. Most of these methods are based on minim…
Training verified learners with learned verifiers
Krishnamurthy Dvijotham, Sven Gowal, Robert Stanforth +4
This paper proposes a new algorithmic framework, predictor-verifier training, to train neural networks that are verifiable, i.e., networks that provably satisfy some desired input-…
Robust Optimization for Electricity Generation
Chaithanya Bandi, Krishnamurthy Dvijotham, David Morton +1
We consider a robust optimization problem in an electric power system under uncertain demand and availability of renewable energy resources. Solving the deterministic alternating c…
A Dual Approach to Scalable Verification of Deep Networks
Krishnamurthy, Dvijotham, Robert Stanforth +3
This paper addresses the problem of formally verifying desirable properties of neural networks, i.e., obtaining provable guarantees that neural networks satisfy specifications rela…