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Martin Vechev
Martin Vechev
Full Professor of Computer Science, ETH Zurich; Scientific Director, INSAIT;
Verified email at inf.ethz.ch - Homepage
Title
Cited by
Cited by
Year
Securify: Practical security analysis of smart contracts
P Tsankov, A Dan, D Drachsler-Cohen, A Gervais, F Buenzli, M Vechev
ACM CCS 2018, 2018
11852018
Ai2: Safety and robustness certification of neural networks with abstract interpretation
T Gehr, M Mirman, D Drachsler-Cohen, P Tsankov, S Chaudhuri, ...
IEEE Symposium on Security and Privacy (SP) 2018, 2018
11282018
An abstract domain for certifying neural networks
G Singh, T Gehr, M Püschel, M Vechev
ACM POPL 2019, 2019
8562019
Code completion with statistical language models
V Raychev, M Vechev, E Yahav
ACM PLDI 2014, 2014
8542014
Fast and Effective Robustness Certification
G Singh, T Gehr, M Mirman, M Püschel, MT Vechev
NeurIPS 2018, 2018
6382018
Differentiable abstract interpretation for provably robust neural networks
M Mirman, T Gehr, M Vechev
ICML 2018, 2018
6252018
Predicting program properties from" big code"
V Raychev, M Vechev, A Krause
ACM POPL 2015, 2015
5242015
Verx: Safety verification of smart contracts
A Permenev, D Dimitrov, P Tsankov, D Drachsler-Cohen, M Vechev
IEEE S&P 2020, 2020
3352020
Probabilistic model for code with decision trees
V Raychev, P Bielik, M Vechev
ACM OOPSLA 2016, 2016
3062016
Learning to fuzz from symbolic execution with application to smart contracts
J He, M Balunović, N Ambroladze, P Tsankov, M Vechev
ACM CCS 2019, 2019
2902019
PHOG: probabilistic model for code
P Bielik, V Raychev, M Vechev
ICML 2016, 0
265*
Boosting Robustness Certification of Neural Networks
G Singh, T Gehr, M Püschel, MT Vechev
ICLR 2019, 2019
2532019
Beyond the single neuron convex barrier for neural network certification
G Singh, R Ganvir, M Püschel, M Vechev
NeurIPS 2019, 2019
2372019
DL2: training and querying neural networks with logic
M Fischer, M Balunovic, D Drachsler-Cohen, T Gehr, C Zhang, M Vechev
ICML 2019, 2019
2112019
Adversarial training and provable defenses: Bridging the gap
M Balunovic, M Vechev
ICLR 2020, 0
198*
PSI: Exact symbolic inference for probabilistic programs
T Gehr, S Misailovic, M Vechev
CAV 2016, 2016
1952016
Learning programs from noisy data
V Raychev, P Bielik, M Vechev, A Krause
ACM POPL 2016, 2016
1932016
Abstraction-guided synthesis of synchronization
M Vechev, E Yahav, G Yorsh
ACM POPL 2010, 2010
1862010
Silq: A high-level quantum language with safe uncomputation and intuitive semantics
B Bichsel, M Baader, T Gehr, M Vechev
ACM PLDI 2020, 2020
1782020
Laws of order: expensive synchronization in concurrent algorithms cannot be eliminated
H Attiya, R Guerraoui, D Hendler, P Kuznetsov, MM Michael, M Vechev
ACM POPL 2011, 2011
1762011
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