This package implements some methods for estimating potential landscapes for non-gradient systems. For a detailed overview of the underlying ideas, please refer to the paper Climbing Escher's stairs: a simple quasi-potential algorithm for weakly non-gradient systems, by Pablo Rodríguez-Sánchez, Egbert van Nes and Marten Scheffer. See readme and examples for more information Changelog: 1.0.3 The readme now points to the reproducible version of the manuscript Minor changes in documentation 1.0.2 Default mode change to 'mixed' (a bit slower, but generates nicer figures) 1.0.1 Documentation updated with links to recently published preprin
International audienceThe efficiency of minimum-energy configuration searching algorithms is closely...
<p>Top row: The population potential landscape ((A) predation model. (B) competition model. (C) mut...
We introduce two new concepts of convergence of gradient systems (Q, Eε, Rε) to a limiting gradient ...
This package implements some methods for estimating potential landscapes for non-gradient systems. ...
This package implements some methods for estimating potential landscapes for non-gradient systems. ...
This package implements some methods for estimating potential landscapes for non-gradient systems. ...
This package implements some methods for estimating potential landscapes for non-gradient systems. ...
Stability landscapes are useful for understanding the properties of dynamical systems. These landsca...
Stability landscapes are useful for understanding the properties of dynamical systems. These landsca...
Motivated by the famous Waddington's epigenetic landscape metaphor in developmental biology, bi...
Schematic representation of the gradient signal implementation in (A) the RD simulations, correspond...
We present the simlandr package for R, which provides a set of tools for constructing potential land...
We develop a theoretical framework for exploring global natures of non-equilibrium dynamical systems...
The system of ordinary differential equations for the method of the gentlest ascent dynamics (GAD) h...
We established the potential and flux landscape theory for evolution. We found explicitly the conven...
International audienceThe efficiency of minimum-energy configuration searching algorithms is closely...
<p>Top row: The population potential landscape ((A) predation model. (B) competition model. (C) mut...
We introduce two new concepts of convergence of gradient systems (Q, Eε, Rε) to a limiting gradient ...
This package implements some methods for estimating potential landscapes for non-gradient systems. ...
This package implements some methods for estimating potential landscapes for non-gradient systems. ...
This package implements some methods for estimating potential landscapes for non-gradient systems. ...
This package implements some methods for estimating potential landscapes for non-gradient systems. ...
Stability landscapes are useful for understanding the properties of dynamical systems. These landsca...
Stability landscapes are useful for understanding the properties of dynamical systems. These landsca...
Motivated by the famous Waddington's epigenetic landscape metaphor in developmental biology, bi...
Schematic representation of the gradient signal implementation in (A) the RD simulations, correspond...
We present the simlandr package for R, which provides a set of tools for constructing potential land...
We develop a theoretical framework for exploring global natures of non-equilibrium dynamical systems...
The system of ordinary differential equations for the method of the gentlest ascent dynamics (GAD) h...
We established the potential and flux landscape theory for evolution. We found explicitly the conven...
International audienceThe efficiency of minimum-energy configuration searching algorithms is closely...
<p>Top row: The population potential landscape ((A) predation model. (B) competition model. (C) mut...
We introduce two new concepts of convergence of gradient systems (Q, Eε, Rε) to a limiting gradient ...