1 citations · 1 across the 4 of their papers we have counts for
4 papers
Beyond Bayesian Inference: The Correlation Integral Likelihood Framework and Gradient Flow Methods for Deterministic Sampling
Piotr Gwiazda, Alexey Kazarnikov, Anna Marciniak-Czochra +1
Calibrating mathematical models of biological processes is essential for achieving predictive accuracy and gaining mechanistic insight. However, this task remains challenging due t…
Statistical parameter identification of mixed-mode patterns from a single experimental snapshot
Alexey Kazarnikov, Robert Scheichl, Irving R. Epstein +2
Parameter identification in pattern formation models from a single experimental snapshot is challenging, as traditional methods often require knowledge of initial conditions or tra…
Parameter estimation for cellular automata
Alexey Kazarnikov, Nadja Ray, Heikki Haario +2
Self-organizing complex systems can be modeled using cellular automaton models. However, the parametrization of these models is crucial and significantly determines the resulting s…
A Bayesian Approach to Modelling Biological Pattern Formation with Limited Data
Alexey Kazarnikov, Robert Scheichl, Heikki Haario +1
Pattern formation in biological tissues plays an important role in the development of living organisms. Since the classical work of Alan Turing, a pre-eminent way of modelling has…