4 citations · 11 across the 8 of their papers we have counts for
9 papers
Computing Actual Causes for Neural Network Predictions under Structured Causal Inputs
Jannick Strobel, Muqsit Azeem, Stefan Leue
Explaining the predictions of neural networks is a central challenge in trustworthy AI. Existing explanation methods, such as those based on feature attribution or minimal sufficie…
Resilient Strategies for Stochastic Systems: How Much Does It Take to Break a Winning Strategy?
Kush Grover, Markel Zubia, Debraj Chakraborty +3
We study the problem of resilient strategies in the presence of uncertainty. Resilient strategies enable an agent to make decisions that are robust against disturbances. In particu…
Sound Value Iteration for Simple Stochastic Games
Muqsit Azeem, Jan Kretinsky, Maximilian Weininger
Algorithmic analysis of Markov decision processes (MDP) and stochastic games (SG) in practice relies on value-iteration (VI) algorithms. Since basic VI does not provide guarantees…
Explainable Representation of Finite-Memory Policies for POMDPs using Decision Trees
Muqsit Azeem, Debraj Chakraborty, Sudeep Kanav +1
Partially Observable Markov Decision Processes (POMDPs) are a fundamental framework for decision-making under uncertainty and partial observability. Since in general optimal polici…
Sound Value Iteration for Simple Stochastic Games
Muqsit Azeem, Jan Kretinsky, Maximilian Weininger
Algorithmic analysis of Markov decision processes (MDP) and stochastic games (SG) in practice relies on value-iteration (VI) algorithms. Since the basic version of VI does not prov…
1-2-3-Go! Policy Synthesis for Parameterized Markov Decision Processes via Decision-Tree Learning and Generalization
Muqsit Azeem, Debraj Chakraborty, Sudeep Kanav +4
Despite the advances in probabilistic model checking, the scalability of the verification methods remains limited. In particular, the state space often becomes extremely large when…
Monitizer: Automating Design and Evaluation of Neural Network Monitors
Muqsit Azeem, Marta Grobelna, Sudeep Kanav +3
The behavior of neural networks (NNs) on previously unseen types of data (out-of-distribution or OOD) is typically unpredictable. This can be dangerous if the network's output is u…
Optimistic and Topological Value Iteration for Simple Stochastic Games
Muqsit Azeem, Alexandros Evangelidis, Jan Křetínský +2
While value iteration (VI) is a standard solution approach to simple stochastic games (SSGs), it suffered from the lack of a stopping criterion. Recently, several solutions have ap…
Direct Construction of Program Alignment Automata for Equivalence Checking
Manish Goyal, Muqsit Azeem, Kumar Madhukar +1
The problem of checking whether two programs are semantically equivalent or not has a diverse range of applications, and is consequently of substantial importance. There are severa…