Bastian Rieck - RankMe

136 papers A* 24B 2Misc 2Journal 88Unranked 16

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Topological Inductive Bias fosters Multiple Instance Learning in Data-Scarce Scenarios. Trans. Mach. Learn. Res. Salome Kazeminia, Carsten Marr, Bastian Rieck
2025	A*	`conf`	Diss-l-ECT: Dissecting Graph Data with Local Euler Characteristic Transforms. ICML Julius von Rohrscheidt, Bastian Rieck
2025	J	`jnl`	EmbedOR: Provable Cluster-Preserving Visualizations with Curvature-Based Stochastic Neighbor Embeddings. CoRR Tristan Luca Saidi, Abigail Hickok, Bastian Rieck, Andrew J. Blumberg
2025	J	`jnl`	From Topology to Retrieval: Decoding Embedding Spaces with Unified Signatures. CoRR Florian Rottach, William Rudman, Bastian Rieck, Harrisen Scells, Carsten Eickhoff
2025	J	`jnl`	Geometry-Aware Edge Pooling for Graph Neural Networks. CoRR Katharina Limbeck, Lydia Mezrag, Guy Wolf, Bastian Rieck
2025	J	`jnl`	Graph and Simplicial Complex Prediction Gaussian Process via the Hodgelet Representations. CoRR Mathieu Alain, So Takao, Xiaowen Dong, Bastian Rieck, Emmanuel Noutahi
2025	J	`jnl`	Homomorphism distortion: A metric to distinguish them all and in the latent space bind them. CoRR Martin Carrasco, Olga Zaghen, Erik J. Bekkers, Bastian Rieck
2025	J	`jnl`	LEAP: Local ECT-Based Learnable Positional Encodings for Graphs. CoRR Juan Amboage, Ernst Röell, Patrick Schnider, Bastian Rieck
2025	J	`jnl`	Less is More: Local Intrinsic Dimensions of Contextual Language Models. CoRR Benjamin Matthias Ruppik, Julius von Rohrscheidt, Carel van Niekerk, Michael Heck, Renato Vukovic, Shutong Feng, Hsien-Chin Lin, Nurul Lubis, Bastian Rieck, Marcus Zibrowius, Milica Gasic
2025	J	`jnl`	Low-dimensional embeddings of high-dimensional data. CoRR Cyril de Bodt, Alex Diaz-Papkovich, Michael Bleher, Kerstin Bunte, Corinna Coupette, Sebastian Damrich, Enrique Fita Sanmartin, Fred A. Hamprecht, Emoke-Ágnes Horvát, Dhruv Kohli, Smita Krishnaswamy, John A. Lee, Boudewijn P. F. Lelieveldt, Leland McInnes, Ian T. Nabney, Maximilian Noichl, Pavlin G. Policar, Bastian Rieck, Guy Wolf, Gal Mishne, Dmitry Kobak
2025	A*	`conf`	MAGNet: Motif-Agnostic Generation of Molecules from Scaffolds. ICLR Leon Hetzel, Johanna Sommer, Bastian Rieck, Fabian J. Theis, Stephan Günnemann
2025	A*	`conf`	MANTRA: The Manifold Triangulations Assemblage. ICLR Rubén Ballester, Ernst Röell, Daniel Bin Schmid, Mathieu Alain, Sergio Escalera, Carles Casacuberta, Bastian Rieck
2025	J	`jnl`	Molecular Machine Learning Using Euler Characteristic Transforms. CoRR Víctor Toscano-Durán, Florian Rottach, Bastian Rieck
2025	A*	`conf`	No Metric to Rule Them All: Toward Principled Evaluations of Graph-Learning Datasets. ICML Corinna Coupette, Jeremy Wayland, Emily Simons, Bastian Rieck
2025	J	`jnl`	No Metric to Rule Them All: Toward Principled Evaluations of Graph-Learning Datasets. CoRR Corinna Coupette, Jeremy Wayland, Emily Simons, Bastian Rieck
2025	Misc	`conf`	Principal Curvatures Estimation with Applications to Single Cell Data. ICASSP Yanlei Zhang, Lydia Mezrag, Xingzhi Sun, Charles Xu, Kincaid MacDonald, Dhananjay Bhaskar, Smita Krishnaswamy, Guy Wolf, Bastian Rieck
2025	J	`jnl`	Principal Curvatures Estimation with Applications to Single Cell Data. CoRR Yanlei Zhang, Lydia Mezrag, Xingzhi Sun, Charles Xu, Kincaid MacDonald, Dhananjay Bhaskar, Smita Krishnaswamy, Guy Wolf, Bastian Rieck
2024	J	`jnl`	All the world's a (hyper)graph: A data drama. Digit. Scholarsh. Humanit. Corinna Coupette, Jilles Vreeken, Bastian Rieck
2024	J	`jnl`	Bayesian Computation Meets Topology. Trans. Mach. Learn. Res. Julius von Rohrscheidt, Bastian Rieck, Sebastian M. Schmon
2024	J	`jnl`	Characterizing Physician Referral Networks with Ricci Curvature. CoRR Jeremy Wayland, Russell J. Funk, Bastian Rieck
2024	—	`conf`	CliquePH: Higher-Order Information for Graph Neural Networks Through Persistent Homology on Clique Graphs. LoG Davide Buffelli, Farzin Soleymani, Bastian Rieck
2024	J	`jnl`	CliquePH: Higher-Order Information for Graph Neural Networks through Persistent Homology on Clique Graphs. CoRR Davide Buffelli, Farzin Soleymani, Bastian Rieck
2024	J	`jnl`	Detecting Spatial Dependence in Transcriptomics Data using Vectorised Persistence Diagrams. CoRR Katharina Limbeck, Bastian Rieck
2024	J	`jnl`	Detecting and Approximating Redundant Computational Blocks in Neural Networks. CoRR Irene Cannistraci, Emanuele Rodolà, Bastian Rieck
2024	A*	`conf`	Differentiable Euler Characteristic Transforms for Shape Classification. ICLR Ernst Röell, Bastian Rieck
2024	J	`jnl`	Diss-l-ECT: Dissecting Graph Data with local Euler Characteristic Transforms. CoRR Julius von Rohrscheidt, Bastian Rieck
2024	J	`jnl`	Generative Topology for Shape Synthesis. CoRR Ernst Röell, Bastian Rieck
2024	J	`jnl`	Graph Classification Gaussian Processes via Hodgelet Spectral Features. CoRR Mathieu Alain, So Takao, Xiaowen Dong, Bastian Rieck, Emmanuel Noutahi
2024	J	`jnl`	MANTRA: The Manifold Triangulations Assemblage. CoRR Rubén Ballester, Ernst Röell, Daniel Bin Schmid, Mathieu Alain, Sergio Escalera, Carles Casacuberta, Bastian Rieck
2024	A*	`conf`	Mapping the Multiverse of Latent Representations. ICML Jeremy Wayland, Corinna Coupette, Bastian Rieck
2024	J	`jnl`	Mapping the Multiverse of Latent Representations. CoRR Jeremy Wayland, Corinna Coupette, Bastian Rieck
2024	A*	`conf`	Metric Space Magnitude for Evaluating the Diversity of Latent Representations. NeurIPS Katharina Limbeck, Rayna Andreeva, Rik Sarkar, Bastian Rieck
2024	—	`conf`	On the Expressivity of Persistent Homology in Graph Learning. LoG Rubén Ballester, Bastian Rieck
2024	J	`jnl`	Persistent Homology via Ellipsoids. CoRR Sara Kalisnik, Bastian Rieck, Ana Zegarac
2024	J	`jnl`	Position Paper: Challenges and Opportunities in Topological Deep Learning. CoRR Theodore Papamarkou, Tolga Birdal, Michael M. Bronstein, Gunnar E. Carlsson, Justin Curry, Yue Gao, Mustafa Hajij, Roland Kwitt, Pietro Liò, Paolo Di Lorenzo, Vasileios Maroulas, Nina Miolane, Farzana Nasrin, Karthikeyan Natesan Ramamurthy, Bastian Rieck, Simone Scardapane, Michael T. Schaub, Petar Velickovic, Bei Wang, Yusu Wang, Guo-Wei Wei, Ghada Zamzmi
2024	A*	`conf`	Position: Topological Deep Learning is the New Frontier for Relational Learning. ICML Theodore Papamarkou, Tolga Birdal, Michael M. Bronstein, Gunnar E. Carlsson, Justin Curry, Yue Gao, Mustafa Hajij, Roland Kwitt, Pietro Lio, Paolo Di Lorenzo, Vasileios Maroulas, Nina Miolane, Farzana Nasrin, Karthikeyan Natesan Ramamurthy, Bastian Rieck, Simone Scardapane, Michael T. Schaub, Petar Velickovic, Bei Wang, Yusu Wang, Guo-Wei Wei, Ghada Zamzmi
2024	A*	`conf`	Simplicial Representation Learning with Neural k-Forms. ICLR Kelly Maggs, Celia Hacker, Bastian Rieck
2024	J	`jnl`	The Manifold Density Function: An Intrinsic Method for the Validation of Manifold Learning. CoRR Benjamin Holmgren, Eli Quist, Jordan Schupbach, Brittany Terese Fasy, Bastian Rieck
2024	J	`jnl`	The magnitude vector of images. J. Appl. Comput. Topol. Michael F. Adamer, Edward De Brouwer, Leslie O'Bray, Bastian Rieck
2024	J	`jnl`	Topology meets Machine Learning: An Introduction using the Euler Characteristic Transform. CoRR Bastian Rieck
2023	—	`conf`	A Diffusion Model Predicts 3D Shapes from 2D Microscopy Images. ISBI Dominik Jens Elias Waibel, Ernst Röell, Bastian Rieck, Raja Giryes, Carsten Marr
2023	J	`jnl`	A Note on Cherry-Picking in Meta-Analyses. Entropy Daisuke Yoneoka, Bastian Rieck
2023	A*	`conf`	Curvature Filtrations for Graph Generative Model Evaluation. NeurIPS Joshua Southern, Jeremy Wayland, Michael M. Bronstein, Bastian Rieck
2023	J	`jnl`	Curvature Filtrations for Graph Generative Model Evaluation. CoRR Joshua Southern, Jeremy Wayland, Michael M. Bronstein, Bastian Rieck
2023	J	`jnl`	DONUT - Creation, Development, and Opportunities of a Database. CoRR Barbara Giunti, Janis Lazovskis, Bastian Rieck
2023	J	`jnl`	Differentiable Euler Characteristic Transforms for Shape Classification. CoRR Ernst Röell, Bastian Rieck
2023	—	`conf`	Euler Characteristic Transform Based Topological Loss for Reconstructing 3D Images from Single 2D Slices. CVPR Workshops Kalyan Varma Nadimpalli, Amit Chattopadhyay, Bastian Rieck
2023	J	`jnl`	Euler Characteristic Transform Based Topological Loss for Reconstructing 3D Images from Single 2D Slices. CoRR Kalyan Varma Nadimpalli, Amit Chattopadhyay, Bastian Rieck
2023	J	`jnl`	Evaluating the "Learning on Graphs" Conference Experience. CoRR Bastian Rieck, Corinna Coupette
2023	J	`jnl`	Filtration Surfaces for Dynamic Graph Classification. CoRR Franz Srambical, Bastian Rieck
2023	—	`conf`	ICML 2023 Topological Deep Learning Challenge: Design and Results. TAG-ML Mathilde Papillon, Mustafa Hajij, Audun Myers, Florian Frantzen, Ghada Zamzmi, Helen Jenne, Johan Mathe, Josef Hoppe, Michael T. Schaub, Theodore Papamarkou, Aldo Guzmán-Sáenz, Bastian Rieck, Neal Livesay, Tamal K. Dey, Abraham Rabinowitz, Aiden Brent, Alessandro Salatiello, Alexander Nikitin, Ali Zia, Claudio Battiloro, Dmitrii Gavrilev, Georg Bökman, German Magai, Gleb Bazhenov, Guillermo Bernárdez, Indro Spinelli, Jens Agerberg, Kalyan Varma Nadimpalli, Lev Telyatnikov, Luca Scofano, Lucia Testa, Manuel Lecha, Maosheng Yang, Mohammed Hassanin, Odin Hoff Gardaa, Olga Zaghen, Paul Häusner, Paul Snopoff, Pavlo Melnyk, Rubén Ballester, Sadrodin Barikbin, Sergio Escalera, Simone Fiorellino, Henry Kvinge, Jan Meissner, Karthikeyan Natesan Ramamurthy, Michael Scholkemper, Paul Rosen, Robin Walters, Shreyas N. Samaga, Soham Mukherjee, Sophia Sanborn, Tegan Emerson, Timothy Doster, Tolga Birdal, Vincent P. Grande, Abdelwahed Khamis, Simone Scardapane, Suraj Singh, Tatiana Malygina, Yixiao Yue, Nina Miolane
2023	J	`jnl`	MAGNet: Motif-Agnostic Generation of Molecules from Shapes. CoRR Leon Hetzel, Johanna Sommer, Bastian Rieck, Fabian J. Theis, Stephan Günnemann
2023	—	`conf`	Metric Space Magnitude and Generalisation in Neural Networks. TAG-ML Rayna Andreeva, Katharina Limbeck, Bastian Rieck, Rik Sarkar
2023	J	`jnl`	Metric Space Magnitude and Generalisation in Neural Networks. CoRR Rayna Andreeva, Katharina Limbeck, Bastian Rieck, Rik Sarkar
2023	J	`jnl`	Metric Space Magnitude for Evaluating Unsupervised Representation Learning. CoRR Katharina Limbeck, Rayna Andreeva, Rik Sarkar, Bastian Rieck
2023	A*	`conf`	Ollivier-Ricci Curvature for Hypergraphs: A Unified Framework. ICLR Corinna Coupette, Sebastian Dalleiger, Bastian Rieck
2023	J	`jnl`	On the Expressivity of Persistent Homology in Graph Learning. CoRR Bastian Rieck
2023	—	`conf`	Preface. TAG-ML Timothy Doster, Tegan Emerson, Henry Kvinge, Nina Miolane, Mathilde Papillon, Bastian Rieck, Sophia Sanborn
2023	J	`jnl`	Simplicial Representation Learning with Neural k-forms. CoRR Kelly Maggs, Celia Hacker, Bastian Rieck
2023	J	`jnl`	Time-Inhomogeneous Diffusion Geometry and Topology. SIAM J. Math. Data Sci. Guillaume Huguet, Alexander Tong, Bastian Rieck, Jessie Huang, Manik Kuchroo, Matthew J. Hirn, Guy Wolf, Smita Krishnaswamy
2023	A*	`conf`	Topological Singularity Detection at Multiple Scales. ICML Julius von Rohrscheidt, Bastian Rieck
2023	—	`ed.`	Topological, Algebraic and Geometric Learning Workshops 2023, 28 July 2023, Honolulu, HI, USA TAG-ML Timothy Doster, Tegan Emerson, Henry Kvinge, Nina Miolane, Mathilde Papillon, Bastian Rieck, Sophia Sanborn
2023	J	`jnl`	Topologically-Regularized Multiple Instance Learning for Red Blood Cell Disease Classification. CoRR Salome Kazeminia, Ario Sadafi, Asya Makhro, Anna Bogdanova, Carsten Marr, Bastian Rieck
2023	J	`jnl`	Weisfeiler and Leman go Machine Learning: The Story so far. J. Mach. Learn. Res. Christopher Morris, Yaron Lipman, Haggai Maron, Bastian Rieck, Nils M. Kriege, Martin Grohe, Matthias Fey, Karsten M. Borgwardt
2023	—	`conf`	Who can Submit an Excellent Review for this Manuscript in the Next 30 Days? - Peer Reviewing in the Age of Overload. JCDL Hamed Alhoori, Edward A. Fox, Ingo Frommholz, Haiming Liu, Corinna Coupette, Bastian Rieck, Tirthankar Ghosal, Jian Wu
2022	J	`jnl`	A Diffusion Model Predicts 3D Shapes from 2D Microscopy Images. CoRR Dominik Jens Elias Waibel, Ernst Röell, Bastian Rieck, Raja Giryes, Carsten Marr
2022	J	`jnl`	All the World's a (Hyper)Graph: A Data Drama. CoRR Corinna Coupette, Jilles Vreeken, Bastian Rieck
2022	J	`jnl`	Capturing Shape Information with Multi-Scale Topological Loss Terms for 3D Reconstruction. CoRR Dominik Jens Elias Waibel, Scott Atwell, Matthias Meier, Carsten Marr, Bastian Rieck
2022	—	`conf`	Capturing Shape Information with Multi-scale Topological Loss Terms for 3D Reconstruction. MICCAI (4) Dominik Jens Elias Waibel, Scott Atwell, Matthias Meier, Carsten Marr, Bastian Rieck
2022	A*	`conf`	Diffusion Curvature for Estimating Local Curvature in High Dimensional Data. NeurIPS Dhananjay Bhaskar, Kincaid MacDonald, Oluwadamilola Fasina, Dawson Thomas, Bastian Rieck, Ian Adelstein, Smita Krishnaswamy
2022	J	`jnl`	Diffusion Curvature for Estimating Local Curvature in High Dimensional Data. CoRR Dhananjay Bhaskar, Kincaid MacDonald, Oluwadamilola Fasina, Dawson Thomas, Bastian Rieck, Ian Adelstein, Smita Krishnaswamy
2022	A*	`conf`	Evaluation Metrics for Graph Generative Models: Problems, Pitfalls, and Practical Solutions. ICLR Leslie O'Bray, Max Horn, Bastian Rieck, Karsten M. Borgwardt
2022	B	`conf`	Exploring the Geometry and Topology of Neural Network Loss Landscapes. IDA Stefan Horoi, Jessie Huang, Bastian Rieck, Guillaume Lajoie, Guy Wolf, Smita Krishnaswamy
2022	—	`ed.`	Learning on Graphs Conference, LoG 2022, 9-12 December 2022, Virtual Event. LoG Bastian Rieck, Razvan Pascanu
2022	J	`jnl`	Ollivier-Ricci Curvature for Hypergraphs: A Unified Framework. CoRR Corinna Coupette, Sebastian Dalleiger, Bastian Rieck
2022	A*	`conf`	On Measuring Excess Capacity in Neural Networks. NeurIPS Florian Graf, Sebastian Zeng, Bastian Rieck, Marc Niethammer, Roland Kwitt
2022	—	`conf`	On the Surprising Behaviour of \textttnode2vec. TAG-ML Celia Hacker, Bastian Rieck
2022	J	`jnl`	On the Surprising Behaviour of node2vec. CoRR Celia Hacker, Bastian Rieck
2022	J	`jnl`	TOAST: Topological Algorithm for Singularity Tracking. CoRR Julius von Rohrscheidt, Bastian Rieck
2022	—	`conf`	Taxonomy of Benchmarks in Graph Representation Learning. LoG Renming Liu, Semih Cantürk, Frederik Wenkel, Sarah McGuire, Xinyi Wang, Anna Little, Leslie O'Bray, Michael Perlmutter, Bastian Rieck, Matthew J. Hirn, Guy Wolf, Ladislav Rampásek
2022	J	`jnl`	Taxonomy of Benchmarks in Graph Representation Learning. CoRR Renming Liu, Semih Cantürk, Frederik Wenkel, Dylan Sandfelder, Devin Kreuzer, Anna Little, Sarah McGuire, Leslie O'Bray, Michael Perlmutter, Bastian Rieck, Matthew J. Hirn, Guy Wolf, Ladislav Rampásek
2022	—	`conf`	The First Learning on Graphs Conference: Preface. LoG Bastian Rieck, Razvan Pascanu, Yuanqi Du, Hannes Stärk, Derek Lim, Chaitanya K. Joshi, Andreea Deac, Iulia Duta, Joshua Robinson, Gabriele Corso, Leonardo Cotta, Yanqiao Zhu, Kexin Huang, Michelle M. Li, Sofia Bourhim, Ilia Igashov
2022	J	`jnl`	Time-inhomogeneous diffusion geometry and topology. CoRR Guillaume Huguet, Alexander Tong, Bastian Rieck, Jessie Huang, Manik Kuchroo, Matthew J. Hirn, Guy Wolf, Smita Krishnaswamy
2022	A*	`conf`	Topological Graph Neural Networks. ICLR Max Horn, Edward De Brouwer, Michael Moor, Yves Moreau, Bastian Rieck, Karsten M. Borgwardt
2021	J	`jnl`	A Survey of Topological Machine Learning Methods. Frontiers Artif. Intell. Felix Hensel, Michael Moor, Bastian Rieck
2021	—	`conf`	A sandbox for prediction and integration of DNA, RNA, and proteins in single cells. NeurIPS Datasets and Benchmarks Malte Lücken, Daniel Burkhardt, Robrecht Cannoodt, Christopher Lance, Aditi Agrawal, Hananeh Aliee, Ann Chen, Louise Deconinck, Angela Detweiler, Alejandro Granados, Shelly Huynh, Laura Isacco, Yang Kim, Dominik Klein, Bony de Kumar, Sunil Kuppasani, Heiko Lickert, Aaron McGeever, Joaquin Melgarejo, Honey Mekonen, Maurizio Morri, Michaela Müller, Norma Neff, Sheryl Paul, Bastian Rieck, Kaylie Schneider, Scott Steelman, Michael Sterr, Daniel Treacy, Alexander Tong, Alexandra-Chloé Villani, Guilin Wang, Jia Yan, Ce Zhang, Angela Pisco, Smita Krishnaswamy, Fabian J. Theis, Jonathan M. Bloom
2021	—	`conf`	Back to the basics with inclusion of clinical domain knowledge - A simple, scalable and effective model of Alzheimer's Disease classification. MLHC Sarah C. Brüningk, Felix Hensel, Louis P. Lukas, Merel Kuijs, Catherine R. Jutzeler, Bastian Rieck
2021	J	`jnl`	Basic Analysis of Bin-Packing Heuristics. CoRR Bastian Rieck
2021	J	`jnl`	Evaluation Metrics for Graph Generative Models: Problems, Pitfalls, and Practical Solutions. CoRR Leslie O'Bray, Max Horn, Bastian Rieck, Karsten M. Borgwardt
2021	A*	`conf`	Filtration Curves for Graph Representation. KDD Leslie O'Bray, Bastian Rieck, Karsten M. Borgwardt
2021	J	`jnl`	Interpretability Aware Model Training to Improve Robustness against Out-of-Distribution Magnetic Resonance Images in Alzheimer's Disease Classification. CoRR Merel Kuijs, Catherine R. Jutzeler, Bastian Rieck, Sarah C. Brüningk
2021	J	`jnl`	Network-guided search for genetic heterogeneity between gene pairs. Bioinform. Anja C. Gumpinger, Bastian Rieck, Dominik G. Grimm, Karsten M. Borgwardt
2021	J	`jnl`	Predicting sepsis in multi-site, multi-national intensive care cohorts using deep learning. CoRR Michael Moor, Nicolas Bennett, Drago Plecko, Max Horn, Bastian Rieck, Nicolai Meinshausen, Peter Bühlmann, Karsten M. Borgwardt
2021	J	`jnl`	Stable topological signatures for metric trees through graph approximations. Pattern Recognit. Lett. Robin Vandaele, Bastian Rieck, Yvan Saeys, Tijl De Bie
2021	J	`jnl`	The magnitude vector of images. CoRR Michael F. Adamer, Leslie O'Bray, Edward De Brouwer, Bastian Rieck, Karsten M. Borgwardt
2021	J	`jnl`	Topological Graph Neural Networks. CoRR Max Horn, Edward De Brouwer, Michael Moor, Yves Moreau, Bastian Rieck, Karsten M. Borgwardt
2021	J	`jnl`	Towards a Taxonomy of Graph Learning Datasets. CoRR Renming Liu, Semih Cantürk, Frederik Wenkel, Dylan Sandfelder, Devin Kreuzer, Anna Little, Sarah McGuire, Leslie O'Bray, Michael Perlmutter, Bastian Rieck, Matthew J. Hirn, Guy Wolf, Ladislav Rampásek
2021	J	`jnl`	Weisfeiler and Leman go Machine Learning: The Story so far. CoRR Christopher Morris, Yaron Lipman, Haggai Maron, Bastian Rieck, Nils M. Kriege, Martin Grohe, Matthias Fey, Karsten M. Borgwardt
2020	J	`jnl`	Accelerating COVID-19 Differential Diagnosis with Explainable Ultrasound Image Analysis. CoRR Jannis Born, Nina Wiedemann, Gabriel Brändle, Charlotte Buhre, Bastian Rieck, Karsten M. Borgwardt
2020	J	`jnl`	Enhancing statistical power in temporal biomarker discovery through representative shapelet mining. Bioinform. Thomas Gumbsch, Christian Bock, Michael Moor, Bastian Rieck, Karsten M. Borgwardt
2020	A*	`conf`	Graph Filtration Learning. ICML Christoph D. Hofer, Florian Graf, Bastian Rieck, Marc Niethammer, Roland Kwitt
2020	J	`jnl`	Graph Kernels: State-of-the-Art and Future Challenges. CoRR Karsten M. Borgwardt, M. Elisabetta Ghisu, Felipe Llinares-López, Leslie O'Bray, Bastian Rieck
2020	J	`jnl`	Graph Kernels: State-of-the-Art and Future Challenges. Found. Trends Mach. Learn. Karsten M. Borgwardt, M. Elisabetta Ghisu, Felipe Llinares-López, Leslie O'Bray, Bastian Rieck
2020	J	`jnl`	Image analysis for Alzheimer's disease prediction: Embracing pathological hallmarks for model architecture design. CoRR Sarah C. Brüningk, Felix Hensel, Catherine R. Jutzeler, Bastian Rieck
2020	J	`jnl`	Path Imputation Strategies for Signature Models. CoRR Michael Moor, Max Horn, Christian Bock, Karsten M. Borgwardt, Bastian Rieck
2020	A*	`conf`	Set Functions for Time Series. ICML Max Horn, Michael Moor, Christian Bock, Bastian Rieck, Karsten M. Borgwardt
2020	A*	`conf`	Topological Autoencoders. ICML Michael Moor, Max Horn, Bastian Rieck, Karsten M. Borgwardt
2020	J	`jnl`	Topological Data Analysis of copy number alterations in cancer. CoRR Stefan Groha, Caroline Weis, Alexander Gusev, Bastian Rieck
2020	J	`jnl`	Topological and kernel-based microbial phenotype prediction from MALDI-TOF mass spectra. Bioinform. Caroline Weis, Max Horn, Bastian Rieck, Aline Cuénod, Adrian Egli, Karsten M. Borgwardt
2020	A*	`conf`	Uncovering the Topology of Time-Varying fMRI Data using Cubical Persistence. NeurIPS Bastian Rieck, Tristan Yates, Christian Bock, Karsten M. Borgwardt, Guy Wolf, Nicholas B. Turk-Browne, Smita Krishnaswamy
2020	J	`jnl`	Uncovering the Topology of Time-Varying fMRI Data using Cubical Persistence. CoRR Bastian Rieck, Tristan Yates, Christian Bock, Karsten M. Borgwardt, Guy Wolf, Nicholas B. Turk-Browne, Smita Krishnaswamy
2019	A*	`conf`	A Persistent Weisfeiler-Lehman Procedure for Graph Classification. ICML Bastian Rieck, Christian Bock, Karsten M. Borgwardt
2019	A*	`conf`	A Wasserstein Subsequence Kernel for Time Series. ICDM Christian Bock, Matteo Togninalli, M. Elisabetta Ghisu, Thomas Gumbsch, Bastian Rieck, Karsten M. Borgwardt
2019	—	`conf`	Early Recognition of Sepsis with Gaussian Process Temporal Convolutional Networks and Dynamic Time Warping. MLHC Michael Moor, Max Horn, Bastian Rieck, Damian Roqueiro, Karsten M. Borgwardt
2019	J	`jnl`	Machine learning for early prediction of circulatory failure in the intensive care unit. CoRR Stephanie L. Hyland, Martin Faltys, Matthias Hüser, Xinrui Lyu, Thomas Gumbsch, Cristóbal Esteban, Christian Bock, Max Horn, Michael Moor, Bastian Rieck, Marc Zimmermann, Dean A. Bodenham, Karsten M. Borgwardt, Gunnar Rätsch, Tobias M. Merz
2019	—	`conf`	Neural Persistence: A Complexity Measure for Deep Neural Networks Using Algebraic Topology. ICLR (Poster) Bastian Rieck, Matteo Togninalli, Christian Bock, Michael Moor, Max Horn, Thomas Gumbsch, Karsten M. Borgwardt
2019	J	`jnl`	Persistent Intersection Homology for the Analysis of Discrete Data. CoRR Bastian Rieck, Markus Banagl, Filip Sadlo, Heike Leitte
2019	J	`jnl`	Set Functions for Time Series. CoRR Max Horn, Michael Moor, Christian Bock, Bastian Rieck, Karsten M. Borgwardt
2019	J	`jnl`	Temporal Convolutional Networks and Dynamic Time Warping can Drastically Improve the Early Prediction of Sepsis. CoRR Michael Moor, Max Horn, Bastian Rieck, Damian Roqueiro, Karsten M. Borgwardt
2019	J	`jnl`	Topological Autoencoders. CoRR Michael Moor, Max Horn, Bastian Rieck, Karsten M. Borgwardt
2019	J	`jnl`	Topological Machine Learning with Persistence Indicator Functions. CoRR Bastian Rieck, Filip Sadlo, Heike Leitte
2019	J	`jnl`	Visualization of Equivalence in 2D Bivariate Fields. Comput. Graph. Forum Boyan Zheng, Bastian Rieck, Heike Leitte, Filip Sadlo
2019	A*	`conf`	Wasserstein Weisfeiler-Lehman Graph Kernels. NeurIPS Matteo Togninalli, M. Elisabetta Ghisu, Felipe Llinares-López, Bastian Rieck, Karsten M. Borgwardt
2019	J	`jnl`	Wasserstein Weisfeiler-Lehman Graph Kernels. CoRR Matteo Togninalli, M. Elisabetta Ghisu, Felipe Llinares-López, Bastian Rieck, Karsten M. Borgwardt
2018	J	`jnl`	Association mapping in biomedical time series via statistically significant shapelet mining. Bioinform. Christian Bock, Thomas Gumbsch, Michael Moor, Bastian Rieck, Damian Roqueiro, Karsten M. Borgwardt
2018	J	`jnl`	Clique Community Persistence: A Topological Visual Analysis Approach for Complex Networks. IEEE Trans. Vis. Comput. Graph. Bastian Rieck, Ulderico Fugacci, Jonas Lukasczyk, Heike Leitte
2018	J	`jnl`	Neural Persistence: A Complexity Measure for Deep Neural Networks Using Algebraic Topology. CoRR Bastian Rieck, Matteo Togninalli, Christian Bock, Michael Moor, Max Horn, Thomas Gumbsch, Karsten M. Borgwardt
2018	J	`jnl`	Visualization of 4D Vector Field Topology. Comput. Graph. Forum Lutz Hofmann, Bastian Rieck, Filip Sadlo
2018	B	`conf`	Visualization of Fullerene Fragmentation. PacificVis Kai Sdeo, Bastian Rieck, Filip Sadlo
2018	Misc	`conf`	Visualization of Parameter Sensitivity of 2D Time-Dependent Flow. ISVC Karsten Hanser, Ole Klein, Bastian Rieck, Bettina Wiebe, Tobias Selz, Marian Piatkowski, Antoni Sagristà, Boyan Zheng, Mária Lukácová-Medvid'ová, George Craig, Heike Leitte, Filip Sadlo
2017	—	`—`	Persistent homology in multivariate data visualization. Bastian Rieck
2016	J	`jnl`	Exploring and Comparing Clusterings of Multivariate Data Sets Using Persistent Homology. Comput. Graph. Forum Bastian Rieck, Heike Leitte
2016	—	`ch.`	Interactive Similarity Analysis and Error Detection in Large Tree Collections. Visualization in Medicine and Life Sciences III Jens Fangerau, Burkhard Höckendorf, Bastian Rieck, Christian Heine, Joachim Wittbrodt, Heike Leitte
2015	J	`jnl`	Persistent Homology for the Evaluation of Dimensionality Reduction Schemes. Comput. Graph. Forum Bastian Rieck, Heike Leitte
2014	J	`jnl`	Structural Analysis of Multivariate Point Clouds Using Simplicial Chains. Comput. Graph. Forum Bastian Rieck, Heike Leitte
2012	J	`jnl`	Multivariate Data Analysis Using Persistence-Based Filtering and Topological Signatures. IEEE Trans. Vis. Comput. Graph. Bastian Rieck, Hubert Mara, Heike Leitte