28 citations · 41 across the 19 of their papers we have counts for
21 papers
Propagate, Then Sharpen: Post-Hoc Refinement of Frozen Node Classifiers
Preben Johnsen Bentdal, Nello Blaser, Xue-Cheng Tai
We study post-hoc refinement of frozen node classifiers: given only the graph and class distributions predicted by a frozen model, can we improve accuracy without access to…
Encoding the Euler Characteristic Transform
Nello Blaser, Odin Hoff Gardaa, Lars M. Salbu +2
The Euler Characteristic Curve (ECC) records the Euler characteristic of a linearly embedded cell complex as a function of filtration height in a given direction, and the Euler Cha…
No Triangulation Without Representation: Generalization in Topological Deep Learning
Johannes S. Schmidt, Martin Carrasco, Ernst Röell +3
Despite an ever-increasing interest in topological deep learning models that target higher-order datasets, there is no consensus on how to evaluate such models. This is exacerbated…
Evaluating Prediction Uncertainty Estimates from BatchEnsemble
Morten Blørstad, Herman Jangsett Mostein, Nello Blaser +1
Deep learning models struggle with uncertainty estimation. Many approaches are either computationally infeasible or underestimate uncertainty. We investigate \textit{BatchEnsemble}…
Reeb Graph of Sample Thickenings
Håvard Bakke Bjerkevik, Nello Blaser, Lars M. Salbu
We consider the Reeb graph of a thickening of points sampled from an unknown space. Our main contribution is a framework to transfer reconstruction results similar to the well-know…
RotaTouille: Rotation Equivariant Deep Learning for Contours
Odin Hoff Gardaa, Nello Blaser
Contours or closed planar curves are common in many domains. For example, they appear as object boundaries in computer vision, isolines in meteorology, and the orbits of rotating m…
Calibrated and uncertain? Evaluating uncertainty estimates in binary classification models
Aurora Grefsrud, Nello Blaser, Trygve Buanes
Rigorous statistical methods, including parameter estimation with accompanying uncertainties, underpin the validity of scientific discovery, especially in the natural sciences. Wit…
Monoidal Rips: Stable Multiparameter Filtrations of Directed Networks
Nello Blaser, Morten Brun, Odin Hoff Gardaa +1
We introduce the monoidal Rips filtration, a filtered simplicial set for weighted directed graphs and other lattice-valued networks. Our construction generalizes the Vietoris-Rips…
SO(3)-Equivariant Neural Networks for Learning from Scalar and Vector Fields on Spheres
Francesco Ballerin, Nello Blaser, Erlend Grong
Analyzing scalar and vector fields on the sphere, such as temperature or wind speed and direction on Earth, is a difficult task. Models should respect both the rotational symmetrie…
Core Bifiltration
Nello Blaser, Morten Brun, Odin Hoff Gardaa +1
The motivation of this paper is to recognize a geometric shape from a noisy sample in the form of a point cloud. Inspired by the HDBSCAN clustering algorithm, we introduce the core…
Stable Update of Regression Trees
Morten Blørstad, Berent Å. S. Lunde, Nello Blaser
Updating machine learning models with new information usually improves their predictive performance, yet, in many applications, it is also desirable to avoid changing the model pre…
Kernelization for Finding Lineal Topologies (Depth-First Spanning Trees) with Many or Few Leaves
Emmanuel Sam, Benjamin Bergougnoux, Petr A. Golovach +1
For a given graph , a depth-first search (DFS) tree of is an -rooted spanning tree such that every edge of is either an edge of or is between a \textit{descen…
ETH-tight algorithms for finding surfaces in simplicial complexes of bounded treewidth
Mitchell Black, Nello Blaser, Amir Nayyeri +1
Given a simplicial complex with simplices, we consider the Connected Subsurface Recognition (c-SR) problem of finding a subcomplex that is homeomorphic to a given connected sur…
The Parameterized Complexity of Finding Minimum Bounded Chains
Nello Blaser, Morten Brun, Lars M. Salbu +1
Finding the smallest -chain with a specific -boundary in a simplicial complex is known as the \textsc{Minimum Bounded Chain} (MBC) problem. The MBC problem is NP-…
Homology Localization Through the Looking-Glass of Parameterized Complexity Theory
Nello Blaser, Erlend Raa Vågset
Finding a cycle of lowest weight that represents a homology class in a simplicial complex is known as homology localization (HL). Here we address this NP-complete problem using par…
Semi Conditional Variational Auto-Encoder for Flow Reconstruction and Uncertainty Quantification from Limited Observations
Kristian Gundersen, Anna Oleynik, Nello Blaser +1
We present a new data-driven model to reconstruct nonlinear flow from spatially sparse observations. The model is a version of a conditional variational auto-encoder (CVAE), which…
Relative persistent homology
Nello Blaser, Morten Brun
The alpha complex efficiently computes persistent homology of a point cloud in Euclidean space when the dimension is low. Given a subset of , relative persistent hom…
Sparse Nerves in Practice
Nello Blaser, Morten Brun
Topological data analysis combines machine learning with methods from algebraic topology. Persistent homology, a method to characterize topological features occurring in data at mu…
Sparse Filtered Nerves
Nello Blaser, Morten Brun
Given a point cloud in Euclidean space and a positive parameter we can consider the -neighborhood of consisting of points at distance less than to . H…
Sparse Dowker Nerves
Nello Blaser, Morten Brun
We propose sparse versions of filtered simplicial complexes used to compte persistent homology of point clouds and of networks. In particular we extend a slight variation of the Sp…
Divisive cover
Nello Blaser, Morten Brun
The aim of this paper is to present a method for computation of persistent homology that performs well at large filtration values. To this end we introduce the concept of filtered…