Krishnamurthy Dvijotham
Krishnamurthy Dvijotham
Research Scientist, DeepMind
Verified email at - Homepage
Cited by
Cited by
A Dual Approach to Scalable Verification of Deep Networks.
K Dvijotham, R Stanforth, S Gowal, TA Mann, P Kohli
UAI 1 (2), 3, 2018
On the effectiveness of interval bound propagation for training verifiably robust models
S Gowal, K Dvijotham, R Stanforth, R Bunel, C Qin, J Uesato, ...
arXiv preprint arXiv:1810.12715, 2018
Inverse optimal control with linearly-solvable MDPs
K Dvijotham, E Todorov
ICML, 2010
Safe exploration in continuous action spaces
G Dalal, K Dvijotham, M Vecerik, T Hester, C Paduraru, Y Tassa
arXiv preprint arXiv:1801.08757, 2018
Real-time optimal power flow
Y Tang, K Dvijotham, S Low
IEEE Transactions on Smart Grid 8 (6), 2963-2973, 2017
Adversarial robustness through local linearization
C Qin, J Martens, S Gowal, D Krishnan, K Dvijotham, A Fawzi, S De, ...
arXiv preprint arXiv:1907.02610, 2019
Training verified learners with learned verifiers
K Dvijotham, S Gowal, R Stanforth, R Arandjelovic, B O'Donoghue, ...
arXiv preprint arXiv:1805.10265, 2018
Achieving verified robustness to symbol substitutions via interval bound propagation
PS Huang, R Stanforth, J Welbl, C Dyer, D Yogatama, S Gowal, ...
arXiv preprint arXiv:1909.01492, 2019
A unified theory of linearly solvable optimal control
K Dvijotham, E Todorov
Uncertainty in Artificial Intelligence, 2012
Scalable verified training for provably robust image classification
S Gowal, KD Dvijotham, R Stanforth, R Bunel, C Qin, J Uesato, ...
Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2019
Error bounds on the DC power flow approximation: A convex relaxation approach
K Dvijotham, DK Molzahn
2016 IEEE 55th Conference on Decision and Control (CDC), 2411-2418, 2016
Opportunities for price manipulation by aggregators in electricity markets
NA Ruhi, K Dvijotham, N Chen, A Wierman
IEEE Transactions on Smart Grid 9 (6), 5687-5698, 2017
A nullspace analysis of the nuclear norm heuristic for rank minimization
K Dvijotham, M Fazel
2010 IEEE International Conference on Acoustics, Speech and Signal …, 2010
Storage sizing and placement through operational and uncertainty-aware simulations
K Dvijotham, M Chertkov, S Backhaus
2014 47th Hawaii international conference on system sciences, 2408-2416, 2014
Linearly solvable optimal control
K Dvijotham, E Todorov
Reinforcement learning and approximate dynamic programming for feedback …, 2012
Operations-based planning for placement and sizing of energy storage in a grid with a high penetration of renewables
K Dvijotham, S Backhaus, M Chertkov
arXiv preprint arXiv:1107.1382, 2011
Convex restriction of power flow feasibility sets
D Lee, HD Nguyen, K Dvijotham, K Turitsyn
IEEE Transactions on Control of Network Systems 6 (3), 1235-1245, 2019
Verification of non-linear specifications for neural networks
C Qin, B O'Donoghue, R Bunel, R Stanforth, S Gowal, J Uesato, ...
arXiv preprint arXiv:1902.09592, 2019
Constructing convex inner approximations of steady-state security regions
HD Nguyen, K Dvijotham, K Turitsyn
IEEE Transactions on Power Systems 34 (1), 257-267, 2018
Convexity of energy-like functions: theoretical results and applications to power system operations
K Dvijotham, S Low, M Chertkov
arXiv preprint arXiv:1501.04052, 2015
The system can't perform the operation now. Try again later.
Articles 1–20