47 citations · 115 across the 33 of their papers we have counts for
39 papers
LSP-DETR: Efficient and Scalable Nuclei Segmentation in Whole-Slide Images
Matěj Pekár, Vít Musil, Rudolf Nenutil +2
Background and Objective: Precise and scalable instance segmentation of cell nuclei is a fundamental prerequisite for computational pathology, yet gigapixel whole-slide images (WSI…
Learning Algorithms for Verification of Markov Decision Processes
Tomáš Brázdil, Krishnendu Chatterjee, Martin Chmelik +6
We present a general framework for applying learning algorithms and heuristical guidance to the verification of Markov decision processes (MDPs). The primary goal of our techniques…
Qualitative Controller Synthesis for Consumption Markov Decision Processes
František Blahoudek, Tomáš Brázdil, Petr Novotný +3
Consumption Markov Decision Processes (CMDPs) are probabilistic decision-making models of resource-constrained systems. In a CMDP, the controller possesses a certain amount of a cr…
Reinforcement Learning of Risk-Constrained Policies in Markov Decision Processes
Tomas Brazdil, Krishnendu Chatterjee, Petr Novotny +1
Markov decision processes (MDPs) are the defacto frame-work for sequential decision making in the presence ofstochastic uncertainty. A classical optimization criterion forMDPs is t…
Deciding Fast Termination for Probabilistic VASS with Nondeterminism
Tomáš Brázdil, Krishnendu Chatterjee, Antonín Kučera +2
A probabilistic vector addition system with states (pVASS) is a finite state Markov process augmented with non-negative integer counters that can be incremented or decremented duri…
Strategy Representation by Decision Trees with Linear Classifiers
Pranav Ashok, Tomáš Brázdil, Krishnendu Chatterjee +3
Graph games and Markov decision processes (MDPs) are standard models in reactive synthesis and verification of probabilistic systems with nondeterminism. The class of -regular w…