Related papers: An Intuitive Automated Modelling Interface for Sys…
In collider physics, experiments are often based on counting the numbers of events in bins of a histogram. We present a new way to build and analyze statistical models that describe these experiments, based on the probabilistic programming…
Industrial computing devices, in particular cyber-physical, real-time and safety-critical systems, focus on reacting to external events and the need to cooperate with other devices to create a functional system. They are often implemented…
We put forth Physiologically Driven Storytelling, a new approach to interactive storytelling where narratives adaptively unfold based on the reader's physiological state. We first describe a taxonomy framing how physiological signals can be…
We present a method for logical specification of the behavior of a system based on the specification of its components and for representing and specifying the effect of a class of communication "signaling pathways" among them. Variations in…
The use of large language models (LLMs) in natural language processing (NLP) tasks is rapidly increasing, leading to changes in how researchers approach problems in the field. To fully utilize these models' abilities, a better understanding…
Survival analysis is central to clinical research, informing patient prognoses, guiding treatment decisions, and optimising resource allocation. Accurate time-to-event predictions not only improve quality of life but also reveal risk…
The auto differentiable simulation is a type of simulation that outputs of the simulation include not only the simulation result itself, but also their derivatives with respect to various input parameters. It provides an efficient method to…
The Invariant Refinement Method for Self Adaptation (IRM-SA) is a design method targeting development of smart Cyber-Physical Systems (sCPS). It allows for a systematic translation of the system requirements into the system architecture…
Given a finite set of words w1,...,wn independently drawn according to a fixed unknown distribution law P called a stochastic language, an usual goal in Grammatical Inference is to infer an estimate of P in some class of probabilistic…
These notes provide a review of basic stochastic population models including branching processes and models of population genetics. Measure-valued population models including superprocesses and Fleming-Viot processes are also introduced…
Mathematical models are increasingly a part of microbiological research. Here, we share our perspective on how modeling advances the discipline by: (i) enforcing logical consistency, (ii) enabling quantitative prediction, (iii) extracting…
The bottom-up construction of synthetic cells is one of the most intriguing and interesting research arenas in synthetic biology. Synthetic cells are built by encapsulating biomolecules inside lipid vesicles (liposomes), allowing the…
Protocells are supposed to have played a key role in the self-organizing processes leading to the emergence of life. Existing models either (i) describe protocell architecture and dynamics, given the existence of sets of collectively…
The Stochastic Calculus of Looping Sequences (SCLS) is a recently proposed modelling language for the representation and simulation of biological systems behaviour. It has been designed with the aim of combining the simplicity of notation…
Computational models are invaluable in capturing the complexities of real-world biological processes. Yet, the selection of appropriate algorithms for inference tasks, especially when dealing with real-world observational data, remains a…
Protein language models (PLMs) have shown promise in improving the understanding of protein sequences, contributing to advances in areas such as function prediction and protein engineering. However, training these models from scratch…
We present the bond-calculus, a process algebra for modelling biological and chemical systems featuring nonlinear dynamics, multiway interactions, and dynamic bonding of agents. Mathematical models based on differential equations have been…
A major bottleneck in developing sustainable processes and materials is a lack of property data. Recently, machine learning approaches have vastly improved previous methods for predicting molecular properties. However, these machine…
Models of complicated systems can be represented in different ways - in scientific papers, they are represented using natural language text as well as equations. But to be of real use, they must also be implemented as software, thus making…
Building custom data analysis platforms traditionally requires extensive software engineering expertise, limiting accessibility for many researchers. Here, I demonstrate that modern large language models (LLMs) and autonomous coding agents…