67 citations · 375 across the 47 of their papers we have counts for
49 papers
Solving the Incompressible Navier-Stokes Equations on Oriented Curved Surfaces Discretized by Point Clouds
Alejandra Foggia, Ivo F. Sbalzarini
We present a meshfree numerical solver for the incompressible Navier-Stokes equations on oriented curved surfaces that are represented by surface point clouds. On curved surfaces,…
Spatiotemporal Control of Charge +1 Topological Defects in Polar Active Matter
Birte C. Geerds, Abhinav Singh, Mathieu Dedenon +4
Topological defects are a conspicuous feature of active liquid crystals that have been associated with important morphogenetic transitions in organismal development. Robust develop…
Robust variable selection for spatial point processes observed with noise
Dominik Sturm, Ivo F. Sbalzarini
We propose a method for variable selection in the intensity function of spatial point processes that combines sparsity-promoting estimation with noise-robust model selection. As hi…
TopoSPAM: Topology grounded Simulation Platform for morphogenesis and biological Active Matter
Abhinav Singh, Abhijeet Krishna, Aboutaleb Amiri +11
We present a topology grounded, multiscale simulation platform for morphogenesis and biological active matter. Morphogenesis and biological active matter represent keystone problem…
An Overview of Meshfree Collocation Methods
Tomas Halada, Serhii Yaskovets, Abhinav Singh +3
We provide a comprehensive overview of meshfree collocation methods for numerically approximating differential operators on continuously labeled unstructured point clouds. Meshfree…
Multivariate Newton Interpolation in Downward Closed Spaces Reaches the Optimal Geometric Approximation Rates for Bos--Levenberg--Trefethen Functions
Michael Hecht, Phil-Alexander Hofmann, Damar Wicaksono +5
We extend the univariate Newton interpolation algorithm to arbitrary spatial dimensions and for any choice of downward-closed polynomial space, while preserving its quadratic runti…
Proven Distributed Memory Parallelization of Particle Methods
Johannes Pahlke, Ivo F. Sbalzarini
We provide a mathematically proven parallelization scheme for particle methods on distributed-memory computer systems. Particle methods are a versatile and widely used class of alg…
Integrating Odeint Time Stepping into OpenFPM for Distributed and GPU Accelerated Numerical Solvers
Abhinav Singh, Landfried Kraatz, Serhii Yaskovets +2
We present a software implementation integrating the time-integration library Odeint from Boost with the OpenFPM framework for scalable scientific computing. This enables compact a…
Learning locally dominant force balances in active particle systems
Dominik Sturm, Suryanarayana Maddu, Ivo F. Sbalzarini
We use a combination of unsupervised clustering and sparsity-promoting inference algorithms to learn locally dominant force balances that explain macroscopic pattern formation in s…
A high-order fully Lagrangian particle level-set method for dynamic surfaces
Lennart J. Schulze, Sachin K. T. Veettill, Ivo F. Sbalzarini
We present a fully Lagrangian particle level-set method based on high-order polynomial regression. This enables closest-point redistancing without requiring a regular Cartesian mes…
An open-source pipeline for solving continuous reaction-diffusion models in image-based geometries of porous media
Justina Stark, Ivo F. Sbalzarini
We present a versatile open-source pipeline for simulating inhomogeneous reaction-diffusion processes in highly resolved, image-based geometries of porous media with reactive bound…
On the Computational Power of Particle Methods
Johannes Pahlke, Ivo F. Sbalzarini
We investigate the computational power of particle methods, a well-established class of algorit hms with applications in scientific computing and computer simulation. The computati…
Roadmap on Deep Learning for Microscopy
Giovanni Volpe, Carolina Wählby, Lei Tian +72
Through digital imaging, microscopy has evolved from primarily being a means for visual observation of life at the micro- and nano-scale, to a quantitative tool with ever-increasin…
Entropically damped artificial compressibility for the discretization corrected particle strength exchange method in incompressible fluid mechanics
Abhinav Singh, Ivo F. Sbalzarini, Anas Obeidat
We present a consistent mesh-free numerical scheme for solving the incompressible Navier-Stokes equations. Our method is based on entropically damped artificial compressibility for…
Adaptive weighting of Bayesian physics informed neural networks for multitask and multiscale forward and inverse problems
Sarah Perez, Suryanarayana Maddu, Ivo F. Sbalzarini +1
In this paper, we present a novel methodology for automatic adaptive weighting of Bayesian Physics-Informed Neural Networks (BPINNs), and we demonstrate that this makes it possible…
Spontaneous flow instabilities of active polar fluids in three dimensions
Abhinav Singh, Quentin Vagne, Frank Jülicher +1
Active polar fluids exhibit spontaneous flow when sufficient active stress is generated by internal molecular mechanisms. This is also referred to as an active Fréedericksz transit…
Global Polynomial Level Sets for Numerical Differential Geometry of Smooth Closed Surfaces
Sachin K. Thekke Veettil, Gentian Zavalani, Uwe Hernandez Acosta +2
We present a computational scheme that derives a global polynomial level set parametrisation for smooth closed surfaces from a regular surface-point set and prove its uniqueness. T…
Corvo: Visualizing CellxGene Single-Cell Datasets in Virtual Reality
Luke Hyman, Ivo F. Sbalzarini, Stephen Quake +1
The CellxGene project has enabled access to single-cell data in the scientific community, providing tools for browsed-based no-code analysis of more than 500 annotated datasets. Ho…
Parallel Compositing of Volumetric Depth Images for Interactive Visualization of Distributed Volumes at High Frame Rates
Aryaman Gupta, Pietro Incardona, Anton Brock +5
We present a parallel compositing algorithm for Volumetric Depth Images (VDIs) of large three-dimensional volume data. Large distributed volume data are routinely produced in both…
Efficient Raycasting of Volumetric Depth Images for Remote Visualization of Large Volumes at High Frame Rates
Aryaman Gupta, Ulrik Günther, Pietro Incardona +4
We present an efficient raycasting algorithm for rendering Volumetric Depth Images (VDIs), and we show how it can be used in a remote visualization setting with VDIs generated and…
A meshfree collocation scheme for surface differential operators on point clouds
Abhinav Singh, Alejandra Foggia, Pietro Incardona +1
We present a meshfree collocation scheme to discretize intrinsic surface differential operators over scalar fields on smooth curved surfaces with given normal vectors and a non-int…
Learning deterministic hydrodynamic equations from stochastic active particle dynamics
Suryanarayana Maddu, Quentin Vagne, Ivo F. Sbalzarini
We present a principled data-driven strategy for learning deterministic hydrodynamic models directly from stochastic non-equilibrium active particle trajectories. We apply our meth…
Parallel Discrete Convolutions on Adaptive Particle Representations of Images
Joel Jonsson, Bevan L. Cheeseman, Suryanarayana Maddu +2
We present data structures and algorithms for native implementations of discrete convolution operators over Adaptive Particle Representations (APR) of images on parallel computer a…
Inverse-Dirichlet Weighting Enables Reliable Training of Physics Informed Neural Networks
Suryanarayana Maddu, Dominik Sturm, Christian L. Müller +1
We characterize and remedy a failure mode that may arise from multi-scale dynamics with scale imbalances during training of deep neural networks, such as Physics Informed Neural Ne…