Marko Vasic

According to our database, Marko Vasic authored at least 15 papers between 2015 and 2022.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2022

MoËT: Mixture of Expert Trees and its application to verifiable reinforcement learning.

Marko Vasic, Andrija Petrovic, Kaiyuan Wang, Mladen Nikolic, Rishabh Singh, Sarfraz Khurshid

Neural Networks, 2022

2021

Programming and Training Rate-Independent Chemical Reaction Networks.

Marko Vasic, Cameron T. Chalk, Austin Luchsinger, Sarfraz Khurshid, David Soloveichik

CoRR, 2021

2020

CRN++: Molecular programming language.

Marko Vasic, David Soloveichik, Sarfraz Khurshid

Nat. Comput., 2020

A study of the learnability of relational properties: model counting meets machine learning (MCML).

Muhammad Usman, Wenxi Wang, Marko Vasic, Kaiyuan Wang, Haris Vikalo, Sarfraz Khurshid

Proceedings of the 41st ACM SIGPLAN International Conference on Programming Language Design and Implementation, 2020

Designing Neural Networks Using Logical Specs.

Shikhar Singh, Marko Vasic, Sarfraz Khurshid

Proceedings of the 31st IEEE International Symposium on Software Reliability Engineering, 2020

Deep Molecular Programming: A Natural Implementation of Binary-Weight ReLU Neural Networks.

Marko Vasic, Cameron T. Chalk, Sarfraz Khurshid, David Soloveichik

Proceedings of the 37th International Conference on Machine Learning, 2020

CRNs Exposed: A Method for the Systematic Exploration of Chemical Reaction Networks.

Marko Vasic, David Soloveichik, Sarfraz Khurshid

Proceedings of the 26th International Conference on DNA Computing and Molecular Programming, 2020

2019

A Study of the Learnability of Relational Properties (Model Counting Meets Machine Learning).

Muhammad Usman, Wenxi Wang, Kaiyuan Wang, Marko Vasic, Haris Vikalo, Sarfraz Khurshid

CoRR, 2019

CRNs Exposed: Systematic Exploration of Chemical Reaction Networks.

Marko Vasic, David Soloveichik, Sarfraz Khurshid

CoRR, 2019

MoËT: Interpretable and Verifiable Reinforcement Learning via Mixture of Expert Trees.

Marko Vasic, Andrija Petrovic, Kaiyuan Wang, Mladen Nikolic, Rishabh Singh, Sarfraz Khurshid

CoRR, 2019

Neural Program Repair by Jointly Learning to Localize and Repair.

Marko Vasic, Aditya Kanade, Petros Maniatis, David Bieber, Rishabh Singh

Proceedings of the 7th International Conference on Learning Representations, 2019

2018

: Molecular Programming Language.

Marko Vasic, David Soloveichik, Sarfraz Khurshid

Proceedings of the DNA Computing and Molecular Programming - 24th International Conference, 2018

2017

File-level vs. module-level regression test selection for .NET.

Marko Vasic, Zuhair Parvez, Aleksandar Milicevic, Milos Gligoric

Proceedings of the 2017 11th Joint Meeting on Foundations of Software Engineering, 2017

Regression test selection across JVM boundaries.

Ahmet Çelik, Marko Vasic, Aleksandar Milicevic, Milos Gligoric

Proceedings of the 2017 11th Joint Meeting on Foundations of Software Engineering, 2017

2015

Porting of run-time environment for Lua-based applications.

Marko Grumic, Marko Vasic, Jelena Kovacevic, Ivan Kastelan

Proceedings of the IEEE 5th International Conference on Consumer Electronics - Berlin, 2015