activity
20222026
most citedSocial Balance on Networks: Local Minima and Best Edge Dynamics

3 citations · 6 across the 12 of their papers we have counts for

collaborators

15 papers

cs.GT2026

Liquid democracy under vote correlation: On the fallacies of averaging and the excluded middle

Seth Gilbert, Stefan Schmid, Santiago Schnell +2

Liquid democracy permits voters to vote directly or delegate their votes to others. Existing algorithmic analyses assign each voter a single scalar parameter, interpreted as an ind…

q-bio.PE2026

Replacers and their evolutionary stability in the Moran process on graphs

Michal Pecho, Jakub Svoboda, Lenka Kopfová +2

Evolutionary dynamics in finite structured populations are commonly modeled by the Moran Birth-death process. A key quantity is the fixation probability of a single invader attempt…

cs.LG2026

Reinforcement Learning for Reachability: Guaranteeing Asymptotic Optimality

Amogh Palasamudram, Jakub Svoboda, Suguman Bansal +1

Reinforcement learning (RL) for reachability specifications is fundamental in sequential decision-making, yet theoretical guarantees remain less explored. A recent work achieves as…

q-bio.PE2026

Genotype specificity and spatial arrangement govern the direction and magnitude of selection in variable environments

Hossein Nemati, Kamran Kaveh, Jakub Svoboda +2

Spatial environmental variation can either amplify or suppress the fixation of beneficial mutants in structured populations, yet the interplay of ecological factors and spatial str…

cs.DC2025

Boosting Payment Channel Network Liquidity with Topology Optimization and Transaction Selection

Krishnendu Chatterjee, Jan Matyáš Křišťan, Stefan Schmid +2

Payment channel networks (PCNs) are a promising technology that alleviates blockchain scalability by shifting the transaction load from the blockchain to the PCN. Nevertheless, the…

cs.AI2025

Value Iteration with Guessing for Markov Chains and Markov Decision Processes

Krishnendu Chatterjee, Mahdi JafariRaviz, Raimundo Saona +1

Two standard models for probabilistic systems are Markov chains (MCs) and Markov decision processes (MDPs). Classic objectives for such probabilistic models for control and plannin…