Related references
Note: Only part of the references are listed.Ensemble-SINDy: Robust sparse model discovery in the low-data, high-noise limit, with active learning and control
U. Fasel et al.
PROCEEDINGS OF THE ROYAL SOCIETY A-MATHEMATICAL PHYSICAL AND ENGINEERING SCIENCES (2022)
Learning mean-field equations from particle data using WSINDy
Daniel A. Messenger et al.
PHYSICA D-NONLINEAR PHENOMENA (2022)
Weak SINDy for partial differential equations
Daniel A. Messenger et al.
JOURNAL OF COMPUTATIONAL PHYSICS (2021)
Learning the dynamics of cell-cell interactions in confined cell migration
David B. Brueckner et al.
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA (2021)
Decomposition of cell activities revealing the role of the cell cycle in driving biofunctional heterogeneity
Tian Lan et al.
SCIENTIFIC REPORTS (2021)
A minimal model for structure, dynamics, and tension of monolayered cell colonies
Debarati Sarkar et al.
COMMUNICATIONS PHYSICS (2021)
Leadership Through Influence: What Mechanisms Allow Leaders to Steer a Swarm?
Sara Bernardi et al.
BULLETIN OF MATHEMATICAL BIOLOGY (2021)
Mean-Field Limits: From Particle Descriptions to Macroscopic Equations
Jose A. Carrillo et al.
ARCHIVE FOR RATIONAL MECHANICS AND ANALYSIS (2021)
WEAK SINDy: GALERKIN-BASED DATA-DRIVEN MODEL SELECTION
Daniel A. Messenger et al.
MULTISCALE MODELING & SIMULATION (2021)
A statistical method for identifying different rules of interaction between individuals in moving animal groups
T. M. Schaerf et al.
JOURNAL OF THE ROYAL SOCIETY INTERFACE (2021)
Learning differential equation models from stochastic agent-based model simulations
John T. Nardini et al.
JOURNAL OF THE ROYAL SOCIETY INTERFACE (2021)
Learning partial differential equations for biological transport models from noisy spatio-temporal data
John H. Lagergren et al.
PROCEEDINGS OF THE ROYAL SOCIETY A-MATHEMATICAL PHYSICAL AND ENGINEERING SCIENCES (2020)
Decoding collective communications using information theory tools
K. R. Pilkiewicz et al.
JOURNAL OF THE ROYAL SOCIETY INTERFACE (2020)
Identifying density-dependent interactions in collective cell behaviour
Alexander P. Browning et al.
JOURNAL OF THE ROYAL SOCIETY INTERFACE (2020)
Al Feynman: A physics-inspired method for symbolic regression
Silviu-Marian Udrescu et al.
SCIENCE ADVANCES (2020)
Data-driven discovery of emergent behaviors in collective dynamics
Ming Zhong et al.
PHYSICA D-NONLINEAR PHENOMENA (2020)
A data-driven method for reconstructing and modelling social interactions in moving animal groups
R. Escobedo et al.
PHILOSOPHICAL TRANSACTIONS OF THE ROYAL SOCIETY B-BIOLOGICAL SCIENCES (2020)
Inferring the Dynamics of Underdamped Stochastic Systems
David B. Brueckner et al.
PHYSICAL REVIEW LETTERS (2020)
Examination of an averaging method for estimating repulsion and attraction interactions in moving groups
Rajnesh K. Mudaliar et al.
PLOS ONE (2020)
Learning and Interpreting Potentials for Classical Hamiltonian Systems
Harish S. Bhat
MACHINE LEARNING AND KNOWLEDGE DISCOVERY IN DATABASES, ECML PKDD 2019, PT I (2020)
Numerical Differentiation of Noisy Data: A Unifying Multi-Objective Optimization Framework
Floris Van Breugel et al.
IEEE ACCESS (2020)
Data-driven discovery of coordinates and governing equations
Kathleen Champion et al.
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA (2019)
Analyzing collective motion with machine learning and topology
Dhananjay Bhaskar et al.
CHAOS (2019)
Using activity and sociability to characterize collective motion
David J. T. Sumpter et al.
PHILOSOPHICAL TRANSACTIONS OF THE ROYAL SOCIETY B-BIOLOGICAL SCIENCES (2018)
Direction-dependent interaction rules enrich pattern formation in an individual-based model of collective behavior
Cole Zmurchok et al.
PLOS ONE (2018)
Robotic Herding of a Flock of Birds Using an Unmanned Aerial Vehicle
Aditya A. Paranjape et al.
IEEE TRANSACTIONS ON ROBOTICS (2018)
Mechanical interactions among followers determine the emergence of leaders in migrating epithelial cell collectives
Medhavi Vishwakarma et al.
NATURE COMMUNICATIONS (2018)
Collective Motion in Human Crowds
William H. Warren
CURRENT DIRECTIONS IN PSYCHOLOGICAL SCIENCE (2018)
Learning partial differential equations via data discovery and sparse optimization
Hayden Schaeffer
PROCEEDINGS OF THE ROYAL SOCIETY A-MATHEMATICAL PHYSICAL AND ENGINEERING SCIENCES (2017)
A mathematical model coupling polarity signaling to cell adhesion explains diverse cell migration patterns
William R. Holmes et al.
PLOS COMPUTATIONAL BIOLOGY (2017)
Semblance of Heterogeneity in Collective Cell Migration
Linus J. Schumacher et al.
CELL SYSTEMS (2017)
Local interactions and global properties of wild, free-ranging stickleback shoals
Ashley J. W. Ward et al.
ROYAL SOCIETY OPEN SCIENCE (2017)
Data-driven discovery of partial differential equations
Samuel H. Rudy et al.
SCIENCE ADVANCES (2017)
Anisotropic interaction rules in circular motions of pigeon flocks: An empirical study based on sparse Bayesian learning
Duxin Chen et al.
PHYSICAL REVIEW E (2017)
Cellular Contraction and Polarization Drive Collective Cellular Motion
Jacob Notbohm et al.
BIOPHYSICAL JOURNAL (2016)
Modeling keratinocyte wound healing dynamics: Cell-cell adhesion promotes sustained collective migration
John T. Nardini et al.
JOURNAL OF THEORETICAL BIOLOGY (2016)
Discovering governing equations from data by sparse identification of nonlinear dynamical systems
Steven L. Brunton et al.
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA (2016)
Anisotropic interactions in a first-order aggregation model
Joep H. M. Evers et al.
NONLINEARITY (2015)
Collective cell migration: guidance principles and hierarchies
Anna Haeger et al.
TRENDS IN CELL BIOLOGY (2015)
Potential of Heterogeneity in Collective Behaviors: A Case Study on Heterogeneous Swarms
Daniela Kengyel et al.
PRIMA 2015: PRINCIPLES AND PRACTICE OF MULTI-AGENT SYSTEMS (2015)
Collective States, Multistability and Transitional Behavior in Schooling Fish
Kolbjorn Tunstrom et al.
PLOS COMPUTATIONAL BIOLOGY (2013)
Understanding cancer stem cell heterogeneity and plasticity
Dean G. Tang
CELL RESEARCH (2012)
Collective motion
Tamas Vicsek et al.
PHYSICS REPORTS-REVIEW SECTION OF PHYSICS LETTERS (2012)
Collective cell guidance by cooperative intercellular forces
Dhananjay T. Tambe et al.
NATURE MATERIALS (2011)
Swarm dynamics and equilibria for a nonlocal aggregation model
R. C. Fetecau et al.
NONLINEARITY (2011)
Inferring the structure and dynamics of interactions in schooling fish
Yael Katz et al.
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA (2011)
Determining interaction rules in animal swarms
Anders Eriksson et al.
BEHAVIORAL ECOLOGY (2010)
Inferring individual rules from collective behavior
Ryan Lukeman et al.
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA (2010)
The Mechanics and Statistics of Active Matter
Sriram Ramaswamy
ANNUAL REVIEW OF CONDENSED MATTER PHYSICS, VOL 1 (2010)
Distilling Free-Form Natural Laws from Experimental Data
Michael Schmidt et al.
SCIENCE (2009)
Interaction ruling animal collective behavior depends on topological rather than metric distance: Evidence from a field study
M. Ballerini et al.
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA (2008)
Emergent behavior in flocks
Felipe Cucker et al.
IEEE TRANSACTIONS ON AUTOMATIC CONTROL (2007)
Complex spatial group patterns result from different animal communication mechanisms
R. Eftimie et al.
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA (2007)
Modelling directional guidance and motility regulation in cell migration
AQ Cai et al.
BULLETIN OF MATHEMATICAL BIOLOGY (2006)
Swarming patterns in a two-dimensional kinematic model for biological groups
CM Topaz et al.
SIAM JOURNAL ON APPLIED MATHEMATICS (2004)
Self-organization in systems of self-propelled particles
H Levine et al.
PHYSICAL REVIEW E (2001)
Share Paper
