Bastian Grossenbacher-Rieck

Geometry-Aware Edge Pooling for Graph Neural Networks

Less is More: Local Intrinsic Dimensions of Contextual Language Models

Shapes, Spaces, Simplices, and Structure: Geometry, Topology, and Machine Learning

Of Shapes and Spaces: Geometry, Topology, and Machine Learning

Vertex, Edge, Clique: What's in a Graph?

NeurIPS 2024: Metric Space Magnitude for Evaluating the Diversity of Latent Representations

Topological Machine Learning II: Topology-Based Graph Learning

Topological Machine Learning I: Features and Kernels

Geometry & Topology in Machine Learning

Digital Emancipation

Curvature for Graph Learning

Topological Machine Learning: Some Applications of Topological Data Analysis

ISBI 23: A Diffusion Model Predicts 3D Shapes from 2D Microscopy Images

The Memory of Persistence

BIRS 2022: Affinity-Aware Graph Networks (Ameya Velingker)

BIRS 2022: Learning to Infer Structures of Network Games (Yan Leng)

BIRS 2022: Multiscale Earth Mover’s Distances (Alex Tong)

MICCAI 22: Capturing Shape Information with Multi-Scale Topological Loss Terms for 3D Reconstruction

BIRS 2022: Flows and Dynamics on Manifolds with Neural ODEs (Smita Krishnaswamy)

BIRS 2022: How Fair is Your Graph? Exploring Fairness Concerns in Neuroimaging Studies (Ira Ktena)

A Good Scale Is Hard To Find: Shape Analysis Using Topology

Neural Sheaf Diffusion: A Topological Perspective on Heterophily and Oversmoothing in GNNs

What are 2D neighbour embeddings of scRNA-seq data actually useful for? (Dmitry Kobak)

Topological Graph Neural Networks

Topology-Based Graph Representation Learning

Recent Advances in Topology-Based Graph Classification

Topological Representation Learning for Structured and Unstructured Data

Uncovering the Topology of Time-Varying fMRI Data using Cubical Persistence (spooky version)

Uncovering the Topology of Time-Varying fMRI Data using Cubical Persistence

Topological Data Analysis for Machine Learning I: Algebraic Topology