← Authors

Bastian Rieck

26 papers · 2019–2025 · 5 conferences · across top CS/AI conferences

Achievements

🌈 Renaissance Researcher (5) πŸŒ‰ Interdisciplinary Bridge πŸ—ΊοΈ Taxonomy Completionist (23) 🐣 Hot Topic Early Bird 🌍 Conference Polyglot (5) πŸƒ Academic Marathon (6) 🧭 Keyword Pioneer 🐝 Cross-Pollinator (14) πŸ‘₯ Mega-Team (22) πŸ‘‘ Triple Crown 🀝 Dynamic Duo (10) πŸ”₯ Unstoppable (7) πŸ—ƒοΈ Keyword Collector (62) πŸ’Ž Century Club (26) ⚑ Prolific Year (5)

Conferences

ICML (9) ICLR (8) NIPS (6) MLHC (2) JMLR (1)

Top co-authors

Karsten Borgwardt (10) Max Horn (6) Michael Moor (5) Christian Bock (4) Corinna Coupette (3) Roland Kwitt (3) Jeremy Wayland (3) Ernst RΓΆell (2) Florian Graf (2) Matteo Togninalli (2)

Keywords

topological data analysis (6) persistent homology (3) graph classification (3) time series classification (2) node feature (2) convolutional neural network (2) graph neural network (2) weisfeiler-lehman algorithm (2) latent representation (2) graph kernel (2) graph representation learning (1) gaussian process (1) random walk (1) intrinsic dimension (1) model compression (1) permutation equivariance (1) alzheimer disease (1) image classification (1) riemannian geometry (1) dynamic time warping (1)

Papers

MANTRA: The Manifold Triangulations Assemblage ICLR 2025
Diss-l-ECT: Dissecting Graph Data with Local Euler Characteristic Transforms ICML 2025
No Metric to Rule Them All: Toward Principled Evaluations of Graph-Learning Datasets ICML 2025
MAGNet: Motif-Agnostic Generation of Molecules from Scaffolds ICLR 2025
Metric Space Magnitude for Evaluating the Diversity of Latent Representations NIPS 2024
Position: Topological Deep Learning is the New Frontier for Relational Learning ICML 2024
Differentiable Euler Characteristic Transforms for Shape Classification ICLR 2024
Simplicial Representation Learning with Neural $k$-Forms ICLR 2024
Mapping the Multiverse of Latent Representations ICML 2024
Topological Singularity Detection at Multiple Scales ICML 2023
Weisfeiler and Leman go Machine Learning: The Story so far JMLR 2023
Curvature Filtrations for Graph Generative Model Evaluation NIPS 2023
Ollivier-Ricci Curvature for Hypergraphs: A Unified Framework ICLR 2023
Evaluation Metrics for Graph Generative Models: Problems, Pitfalls, and Practical Solutions ICLR 2022
Topological Graph Neural Networks ICLR 2022
Diffusion Curvature for Estimating Local Curvature in High Dimensional Data NIPS 2022
On Measuring Excess Capacity in Neural Networks NIPS 2022
Back to the basics with inclusion of clinical domain knowledge - A simple, scalable and effective model of Alzheimer’s Disease classification MLHC 2021
Graph Filtration Learning ICML 2020
Uncovering the Topology of Time-Varying fMRI Data using Cubical Persistence NIPS 2020
Set Functions for Time Series ICML 2020
Topological Autoencoders ICML 2020
Wasserstein Weisfeiler-Lehman Graph Kernels NIPS 2019
A Persistent Weisfeiler-Lehman Procedure for Graph Classification ICML 2019
Neural Persistence: A Complexity Measure for Deep Neural Networks Using Algebraic Topology ICLR 2019
Early Recognition of Sepsis with Gaussian Process Temporal Convolutional Networks and Dynamic Time Warping MLHC 2019