1 citations · 2 across the 6 of their papers we have counts for
6 papers
A bibliometric study on mathematical oncology: interdisciplinarity, internationality, collaboration and trending topics
Kira Pugh, Linnéa Gyllingberg, Stanislav Stratiev +1
Mathematical oncology is an interdisciplinary research field where the mathematical sciences meet cancer research. Being situated at the intersection of these two fields makes math…
Cognition without neurons: modelling anticipation in a basal reservoir computer
Polyphony Bruna, Linnéa Gyllingberg
How do non-neural organisms, such as the slime mould \textit{Physarum polycephalum}, anticipate periodic events in their environment? We present a minimal, biologically inspired re…
A minimal model of cognition based on oscillatory and current-based reinforcement processes
Linnéa Gyllingberg, Yu Tian, David J. T. Sumpter
Building mathematical models of brains is difficult because of the sheer complexity of the problem. One potential starting point is through basal cognition, which gives abstract re…
Using neuronal models to capture burst and glide motion and leadership in fish
Linnéa Gyllingberg, Alex Szorkovszky, David J. T. Sumpter
While mathematical models, in particular self-propelled particle (SPP) models, capture many of the observed properties of large fish schools, they do not always capture the interac…
Finding analytical approximations for discrete, stochastic, individual-based models of ecology
Linnéa Gyllingberg, David J. T. Sumpter, Åke Brännström
Discrete time, spatially extended models play an important role in ecology, modelling population dynamics of species ranging from micro-organisms to birds. An important question is…
The Lost Art of Mathematical Modelling
Linnéa Gyllingberg, Abeba Birhane, David J. T. Sumpter
We provide a critique of mathematical biology in light of rapid developments in modern machine learning. We argue that out of the three modelling activities -- (1) formulating mode…