Stellar
Bastian Rieck, Frank H. Lutz, (2025) | Data set
Topology meets Machine Learning: An Introduction using the Euler Characteristic Transform
Notices of the American Mathematical Society (2025) | Article
Principal Curvatures Estimation with Applications to Single Cell Data
Zhang, Yanlei and Mezrag, Lydia and Sun, Xingzhi and Xu, Charles and Macdonald, Kincaid and Bhaskar, Dhananjay and Krishnaswamy, Smita and Wolf, Guy and Rieck, Bastian,
ICASSP 2025 - 2025 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP): IEEE
(6.4.2025) | Conférence
MAGNet: Motif-Agnostic Generation of Molecules from Scaffolds
Leon Hetzel and Johanna Sommer and Bastian Rieck and Fabian Theis and Stephan Günnemann,
International Conference on Learning Representations:
(2025) | Conférence
MANTRA: The Manifold Triangulations Assemblage
Rubén Ballester and Ernst Röell and Daniel Bin Schmid and Mathieu Alain and Sergio Escalera and Carles Casacuberta and Bastian Rieck,
International Conference on Learning Representations:
(2025) | Conférence
Characterizing Physician Referral Networks with Ricci Curvature
Jeremy Wayland, Russell J. Funk, Bastian Rieck (2025)
| Chapitre de livre
CliquePH: Higher-Order Information for Graph Neural Networks through Persistent Homology on Clique Graphs
Davide Buffelli and Farzin Soleymani and Bastian Rieck,
Proceedings of the Third Learning on Graphs Conference: PMLR
(2025) | Conférence
On the Expressivity of Persistent Homology in Graph Learning
Rubén Ballester and Bastian Rieck,
Proceedings of the Third Learning on Graphs Conference: PMLR
(2025) | Conférence
The magnitude vector of images
Journal of Applied and Computational Topology (2024) | Article
Enhancing the diagnosis of functionally relevant coronary artery disease with machine learning
Nature Communications (2024) | Article
Advancing Precision Medicine: Algebraic Topology and Differential Geometry in Radiology and Computational Pathology
Laboratory Investigation (2024) | Article
Mapping the Multiverse of Latent Representations
Wayland, Jeremy and Coupette, Corinna and Rieck, Bastian,
Proceedings of the 41st International Conference on Machine Learning: PMLR
(2024) | Conférence
Position: Topological Deep Learning is the New Frontier for Relational Learning
Papamarkou, Theodore and Birdal, Tolga and Bronstein, Michael M. and Carlsson, Gunnar E. and Curry, Justin and Gao, Yue and Hajij, Mustafa and Kwitt, Roland and Lio, Pietro and Di Lorenzo, Paolo and Maroulas, Vasileios and Miolane, Nina and Nasrin, Farzana and Natesan Ramamurthy, Karthikeyan and Rieck, Bastian and Scardapane, Simone and Schaub, Michael T and Veličkovic, Petar and Wang, Bei and Wang, Yusu and Wei, Guowei and Zamzmi, Ghada,
Proceedings of the 41st International Conference on Machine Learning: PMLR
(2024) | Conférence
Simplicial Representation Learning with Neural $k$-Forms
Kelly Maggs and Celia Hacker and Bastian Rieck,
The Twelfth International Conference on Learning Representations:
(2024) | Conférence
Differentiable Euler Characteristic Transforms for Shape Classification
Ernst Röell and Bastian Rieck,
The Twelfth International Conference on Learning Representations:
(2024) | Conférence
Metric Space Magnitude for Evaluating the Diversity of Latent Representations
Katharina Limbeck and Rayna Andreeva and Rik Sarkar and Bastian Rieck,
Advances in Neural Information Processing Systems: Curran Associates, Inc.
(2024) | Conférence
Bayesian Computation Meets Topology
Transactions on Machine Learning Research (2024) | Article
All the world’s a (hyper)graph: A data drama
Digital Scholarship in the Humanities (2023) | Article
Predicting sepsis using deep learning across international sites: a retrospective development and validation study
eClinicalMedicine (2023) | Article
Who can Submit an Excellent Review for this Manuscript in the Next 30 Days? - Peer Reviewing in the Age of Overload
Alhoori, Hamed and Fox, Edward A. and Frommholz, Ingo and Liu, Haiming and Coupette, Corinna and Rieck, Bastian A. and Ghosal, Tirthankar and Wu, Jian,
2023 ACM/IEEE Joint Conference on Digital Libraries (JCDL): IEEE
(6.2023) | Conférence
Time-Inhomogeneous Diffusion Geometry and Topology
SIAM Journal on Mathematics of Data Science (2023) | Article
Single-cell analysis reveals inflammatory interactions driving macular degeneration
Nature Communications (2023) | Article
Cell cycle controls long-range calcium signaling in the regenerating epidermis
Journal of Cell Biology (2023) | Article
A Note on Cherry-Picking in Meta-Analyses
Entropy (2023) | Article
A Diffusion Model Predicts 3D Shapes from 2D Microscopy Images
Waibel, Dominik J. E. and Röell, Ernst and Rieck, Bastian and Giryes, Raja and Marr, Carsten,
2023 IEEE 20th International Symposium on Biomedical Imaging (ISBI): IEEE
(18.4.2023) | Conférence
Neurospectrum: A Geometric and Topological Deep Learning Framework for Uncovering Spatiotemporal Signatures in Neural Activity
Dhananjay Bhaskar, Yanlei Zhang, Jessica L Moore, Feng Gao, Bastian Rieck, Guy Wolf, Firas Khasawneh, Elizabeth Munch, J. Adam Noah, Helen Pushkarskaya, Christopher Pittenger, Valentina Greco, Smita Krishnaswamy, Jessica Moore, (2023) | Prépublication
Curvature Filtrations for Graph Generative Model Evaluation
Southern, Joshua and Wayland, Jeremy and Bronstein, Michael and Rieck, Bastian,
Advances in Neural Information Processing Systems: Curran Associates, Inc.
(2023) | Conférence
Weisfeiler and Leman go Machine Learning: The Story so far
Journal of Machine Learning Research (2023) | Article
Ollivier-Ricci Curvature for Hypergraphs: A Unified Framework
Corinna Coupette and Sebastian Dalleiger and Bastian Rieck,
The Eleventh International Conference on Learning Representations :
(2023) | Conférence
Topological Singularity Detection at Multiple Scales
Von Rohrscheidt, Julius and Rieck, Bastian,
Proceedings of the 40th International Conference on Machine Learning: PMLR
(2023) | Conférence
Multiscale PHATE identifies multimodal signatures of COVID-19
Nature Biotechnology (2022) | Article
Direct antimicrobial resistance prediction from clinical MALDI-TOF mass spectra using machine learning
Nature Medicine (2022) | Article
Diffusion Curvature for Estimating Local Curvature in High Dimensional Data
Advances in Neural Information Processing Systems:
(2022) | Conférence
Evaluation Metrics for Graph Generative Models: Problems, Pitfalls, and Practical Solutions
International Conference on Learning Representations:
(2022) | Conférence
On Measuring Excess Capacity in Neural Networks
Advances in Neural Information Processing Systems:
(2022) | Conférence
Topological Graph Neural Networks
International Conference on Learning Representations:
(2022) | Conférence
Capturing Shape Information with Multi-scale Topological Loss Terms for 3D Reconstruction
, dans Medical Image Computing and Computer Assisted Intervention – MICCAI 2022
Waibel, Dominik J. E. and Atwell, Scott and Meier, Matthias and Marr, Carsten and Rieck, Bastian (Springer Nature Switzerland, 2022), ISBN: 9783031164408
| Chapitre de livre
Exploring the Geometry and Topology of Neural Network Loss Landscapes
, dans Advances in Intelligent Data Analysis XX
Horoi, Stefan and Huang, Jessie and Rieck, Bastian and Lajoie, Guillaume and Wolf, Guy and Krishnaswamy, Smita (Springer International Publishing, 2022), ISBN: 9783031013331
| Chapitre de livre
Taxonomy of Benchmarks in Graph Representation Learning
Liu, Renming and Cantürk, Semih and Wenkel, Frederik and McGuire, Sarah and Wang, Xinyi and Little, Anna and Bray, Leslie Oand Perlmutter, Michael and Rieck, Bastian and Hirn, Matthew and Wolf, Guy and Rampášek, Ladislav,
Proceedings of the First Learning on Graphs Conference: PMLR
(2022) | Conférence
DRIAMS: Database of Resistance Information on Antimicrobials and MALDI-TOF Mass Spectra
Caroline, Aline Cuénod, Bastian Rieck, Karsten Borgwardt, Adrian Egli, Caroline Weis, (2021) | Data set
Filtration Curves for Graph Representation
O’Bray, Leslie and Rieck, Bastian and Borgwardt, Karsten,
Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery & Data Mining: ACM
(14.8.2021) | Conférence
Stable topological signatures for metric trees through graph approximations
Pattern Recognition Letters (2021) | Article
Early Prediction of Sepsis in the ICU Using Machine Learning: A Systematic Review
Frontiers in Medicine (2021) | Article
A Survey of Topological Machine Learning Methods
Frontiers in Artificial Intelligence (2021) | Article
Accelerating Detection of Lung Pathologies with Explainable Ultrasound Image Analysis
Applied Sciences (2021) | Article
Back to the basics with inclusion of clinical domain knowledge - A simple, scalable and effective model of Alzheimer’s Disease classification
Brüningk, Sarah C. and Hensel, Felix and Lukas, Louis P. and Kuijs, Merel and Jutzeler, Catherine R. and Rieck, Bastian,
Proceedings of the 6th Machine Learning for Healthcare Conference: PMLR
(2021) | Conférence
Enhancing statistical power in temporal biomarker discovery through representative shapelet mining
Bioinformatics (2020) | Article
Comorbidities, clinical signs and symptoms, laboratory findings, imaging features, treatment strategies, and outcomes in adult and pediatric patients with COVID-19: A systematic review and meta-analysis
Travel Medicine and Infectious Disease (2020) | Article
Topological and kernel-based microbial phenotype prediction from MALDI-TOF mass spectra
Bioinformatics (2020) | Article
Network-guided search for genetic heterogeneity between gene pairs
Bioinformatics (2020) | Article
Early prediction of circulatory failure in the intensive care unit using machine learning
Nature Medicine (2020) | Article
Topological Machine Learning with Persistence Indicator Functions
, dans Topological Methods in Data Analysis and Visualization V
Rieck, Bastian and Sadlo, Filip and Leitte, Heike (Springer International Publishing, 2020), ISBN: 9783030430368
| Chapitre de livre
Hierarchies and Ranks for Persistence Pairs
, dans Topological Methods in Data Analysis and Visualization V
Rieck, Bastian and Sadlo, Filip and Leitte, Heike (Springer International Publishing, 2020), ISBN: 9783030430368
| Chapitre de livre
Graph Kernels: State-of-the-Art and Future Challenges
Foundations and Trends® in Machine Learning (2020) | Article
Persistence Concepts for 2D Skeleton Evolution Analysis
, dans Topological Methods in Data Analysis and Visualization V
Rieck, Bastian and Sadlo, Filip and Leitte, Heike (Springer International Publishing, 2020), ISBN: 9783030430368
| Chapitre de livre
Persistent Intersection Homology for the Analysis of Discrete Data
, dans Topological Methods in Data Analysis and Visualization V
Rieck, Bastian and Banagl, Markus and Sadlo, Filip and Leitte, Heike (Springer International Publishing, 2020), ISBN: 9783030430368
| Chapitre de livre
Uncovering the Topology of Time-Varying fMRI Data using Cubical Persistence
Rieck, Bastian and Yates, Tristan and Bock, Christian and Borgwardt, Karsten and Wolf, Guy and Turk-Browne, Nicholas and Krishnaswamy, Smita,
Advances in Neural Information Processing Systems: Curran Associates, Inc.
(2020) | Conférence
Graph Filtration Learning
Hofer, Christoph and Graf, Florian and Rieck, Bastian and Niethammer, Marc and Kwitt, Roland,
Proceedings of the 37th International Conference on Machine Learning: PMLR
(2020) | Conférence
Topological Autoencoders
Moor, Michael and Horn, Max and Rieck, Bastian and Borgwardt, Karsten,
Proceedings of the 37th International Conference on Machine Learning: PMLR
(2020) | Conférence
Set Functions for Time Series
Horn, Max and Moor, Michael and Bock, Christian and Rieck, Bastian and Borgwardt, Karsten,
Proceedings of the 37th International Conference on Machine Learning: PMLR
(2020) | Conférence
A Wasserstein Subsequence Kernel for Time Series
Bock, Christian and Togninalli, Matteo and Ghisu, Elisabetta and Gumbsch, Thomas and Rieck, Bastian and Borgwardt, Karsten,
2019 IEEE International Conference on Data Mining (ICDM): IEEE
(11.2019) | Conférence
Visualization of Equivalence in 2D Bivariate Fields
Computer Graphics Forum (2019) | Article
A Persistent Weisfeiler-Lehman Procedure for Graph Classification
Rieck, Bastian and Bock, Christian and Borgwardt, Karsten,
Proceedings of the 36th International Conference on Machine Learning: PMLR
(2019) | Conférence
Wasserstein Weisfeiler-Lehman Graph Kernels
Togninalli, Matteo and Ghisu, Elisabetta and Llinares-López, Felipe and Rieck, Bastian and Borgwardt, Karsten,
Advances in Neural Information Processing Systems: Curran Associates, Inc.
(2019) | Conférence
Neural Persistence: A Complexity Measure for Deep Neural Networks Using Algebraic Topology
Bastian Rieck and Matteo Togninalli and Christian Bock and Michael Moor and Max Horn and Thomas Gumbsch and Karsten Borgwardt,
International Conference on Learning Representations:
(2019) | Conférence
Early Recognition of Sepsis with Gaussian Process Temporal Convolutional Networks and Dynamic Time Warping
Moor, Michael and Horn, Max and Rieck, Bastian and Roqueiro, Damian and Borgwardt, Karsten,
Proceedings of the 4th Machine Learning for Healthcare Conference: PMLR
(2019) | Conférence
Association mapping in biomedical time series via statistically significant shapelet mining
Bioinformatics (2018) | Article
Visualization of 4D Vector Field Topology
Computer Graphics Forum (2018) | Article
Visualization of Fullerene Fragmentation
Sdeo, Kai and Rieck, Bastian and Sadlo, Filip,
2018 IEEE Pacific Visualization Symposium (PacificVis): IEEE
(4.2018) | Conférence
Clique Community Persistence: A Topological Visual Analysis Approach for Complex Networks
IEEE Transactions on Visualization and Computer Graphics (2018) | Article
Visualization of Parameter Sensitivity of 2D Time-Dependent Flow
, dans Advances in Visual Computing
Hanser, Karsten and Klein, Ole and Rieck, Bastian and Wiebe, Bettina and Selz, Tobias and Piatkowski, Marian and Sagristà, Antoni and Zheng, Boyan and Lukácová-Medvidová, Mária and Craig, George and Leitte, Heike and Sadlo, Filip (Springer International Publishing, 2018), ISBN: 9783030038014
| Chapitre de livre
