Karsten M. Borgwardt

ORCID

Publication Activity (10 Years)

Years Active: 2005-2024
Publications (10 Years): 71

Top Venues

Publications

Paolo Pellizzoni, Carlos G. Oliver, Karsten M. Borgwardt
Structure- and Function-Aware Substitution Matrices via Learnable Graph Matching. RECOMB (2024)
Dexiong Chen, Philip Hartout, Paolo Pellizzoni, Carlos G. Oliver, Karsten M. Borgwardt
Endowing Protein Language Models with Structural Knowledge. CoRR (2024)
Dexiong Chen, Till Hendrik Schulz, Karsten M. Borgwardt
Learning Long Range Dependencies on Graphs via Random Walks. CoRR (2024)
Giovanni Visonà, Diane Duroux, Lucas Miranda, Emese Sükei, Yiran Li, Karsten M. Borgwardt, Carlos G. Oliver
Multimodal learning in clinical proteomics: enhancing antimicrobial resistance prediction models with chemical information. Bioinform. 39 (12) (2023)
Paolo Pellizzoni, Giulia Muzio, Karsten M. Borgwardt
Higher-order genetic interaction discovery with network-based biological priors. Bioinform. 39 (Supplement-1) (2023)
Dexiong Chen, Paolo Pellizzoni, Karsten M. Borgwardt
Fisher Information Embedding for Node and Graph Learning. CoRR (2023)
Paolo Pellizzoni, Karsten M. Borgwardt
FASM and FAST-YB: Significant Pattern Mining with False Discovery Rate Control. ICDM (2023)
Dexiong Chen, Bowen Fan, Carlos G. Oliver, Karsten M. Borgwardt
Unsupervised Manifold Alignment with Joint Multidimensional Scaling. ICLR (2023)
Dexiong Chen, Paolo Pellizzoni, Karsten M. Borgwardt
Fisher Information Embedding for Node and Graph Learning. ICML (2023)
Michael F. Adamer, Eljas Roellin, Lucie Bourguignon, Karsten M. Borgwardt
SIMBSIG: similarity search and clustering for biobank-scale data. Bioinform. 39 (1) (2023)
Tim Kucera, Carlos G. Oliver, Dexiong Chen, Karsten M. Borgwardt
ProteinShake: Building datasets and benchmarks for deep learning on protein structures. NeurIPS (2023)
Max Horn, Edward De Brouwer, Michael Moor, Yves Moreau, Bastian Rieck, Karsten M. Borgwardt
Topological Graph Neural Networks. ICLR (2022)
Carlos G. Oliver, Dexiong Chen, Vincent Mallet, Pericles Philippopoulos, Karsten M. Borgwardt
Approximate Network Motif Mining Via Graph Learning. CoRR (2022)
Dexiong Chen, Leslie O'Bray, Karsten M. Borgwardt
Structure-Aware Transformer for Graph Representation Learning. ICML (2022)
Dexiong Chen, Bowen Fan, Carlos G. Oliver, Karsten M. Borgwardt
Unsupervised Manifold Alignment with Joint Multidimensional Scaling. CoRR (2022)
Leslie O'Bray, Max Horn, Bastian Rieck, Karsten M. Borgwardt
Evaluation Metrics for Graph Generative Models: Problems, Pitfalls, and Practical Solutions. ICLR (2022)
Dexiong Chen, Leslie O'Bray, Karsten M. Borgwardt
Structure-Aware Transformer for Graph Representation Learning. CoRR (2022)
Leslie O'Bray, Bastian Rieck, Karsten M. Borgwardt
Filtration Curves for Graph Representation. KDD (2021)
Michael Moor, Nicolas Bennett, Drago Plecko, Max Horn, Bastian Rieck, Nicolai Meinshausen, Peter Bühlmann, Karsten M. Borgwardt
Predicting sepsis in multi-site, multi-national intensive care cohorts using deep learning. CoRR (2021)
Michael F. Adamer, Leslie O'Bray, Edward De Brouwer, Bastian Rieck, Karsten M. Borgwardt
The magnitude vector of images. CoRR (2021)
Anja C. Gumpinger, Bastian Rieck, Dominik G. Grimm, Karsten M. Borgwardt
Network-guided search for genetic heterogeneity between gene pairs. Bioinform. 37 (1) (2021)
Max Horn, Edward De Brouwer, Michael Moor, Yves Moreau, Bastian Rieck, Karsten M. Borgwardt
Topological Graph Neural Networks. CoRR (2021)
Leslie O'Bray, Max Horn, Bastian Rieck, Karsten M. Borgwardt
Evaluation Metrics for Graph Generative Models: Problems, Pitfalls, and Practical Solutions. CoRR (2021)
Giulia Muzio, Leslie O'Bray, Karsten M. Borgwardt
Biological network analysis with deep learning. Briefings Bioinform. 22 (2) (2021)
Christopher Morris, Yaron Lipman, Haggai Maron, Bastian Rieck, Nils M. Kriege, Martin Grohe, Matthias Fey, Karsten M. Borgwardt
Weisfeiler and Leman go Machine Learning: The Story so far. CoRR (2021)
Karsten M. Borgwardt, M. Elisabetta Ghisu, Felipe Llinares-López, Leslie O'Bray, Bastian Rieck
Graph Kernels: State-of-the-Art and Future Challenges. CoRR (2020)
Michael Moor, Max Horn, Bastian Rieck, Karsten M. Borgwardt
Topological Autoencoders. ICML (2020)
Matteo Togninalli, Ümit Seren, Jan A. Freudenthal, J. Grey Monroe, Dazhe Meng, Magnus Nordborg, Detlef Weigel, Karsten M. Borgwardt, Arthur Korte, Dominik G. Grimm
. Nucleic Acids Res. 48 (Database-Issue) (2020)
Bastian Rieck, Tristan Yates, Christian Bock, Karsten M. Borgwardt, Guy Wolf, Nicholas B. Turk-Browne, Smita Krishnaswamy
Uncovering the Topology of Time-Varying fMRI Data using Cubical Persistence. NeurIPS (2020)
Jannis Born, Nina Wiedemann, Gabriel Brändle, Charlotte Buhre, Bastian Rieck, Karsten M. Borgwardt
Accelerating COVID-19 Differential Diagnosis with Explainable Ultrasound Image Analysis. CoRR (2020)
Xiao He, Thomas Gumbsch, Damian Roqueiro, Karsten M. Borgwardt
Kernel conditional clustering and kernel conditional semi-supervised learning. Knowl. Inf. Syst. 62 (3) (2020)
Bastian Rieck, Tristan Yates, Christian Bock, Karsten M. Borgwardt, Guy Wolf, Nicholas B. Turk-Browne, Smita Krishnaswamy
Uncovering the Topology of Time-Varying fMRI Data using Cubical Persistence. CoRR (2020)
Anja C. Gumpinger, Kasper Lage, Heiko Horn, Karsten M. Borgwardt
Prediction of cancer driver genes through network-based moment propagation of mutation scores. Bioinform. 36 (Supplement-1) (2020)
Max Horn, Michael Moor, Christian Bock, Bastian Rieck, Karsten M. Borgwardt
Set Functions for Time Series. ICML (2020)
Adrian Egli, Manuel Battegay, Andrea C. Büchler, Peter Bühlmann, Thierry Calandra, Philippe Eckert, Hansjakob Furrer, Gilbert Greub, Stephan M. Jakob, Laurent Kaiser, Stephen L. Leib, Stephan Marsch, Nicolai Meinshausen, Jean-Luc Pagani, Jerome Pugin, Gunnar Rätsch, Jacques Schrenzel, Reto Schüpbach, Martin Siegemund, Nicola Zamboni, Reinhard Zbinden, Annelies Zinkernagel, Karsten M. Borgwardt
SPHN/PHRT: Forming a Swiss-Wide Infrastructure for Data-Driven Sepsis Research. MIE (2020)
Michael Moor, Max Horn, Christian Bock, Karsten M. Borgwardt, Bastian Rieck
Path Imputation Strategies for Signature Models. CoRR (2020)
Karsten M. Borgwardt, M. Elisabetta Ghisu, Felipe Llinares-López, Leslie O'Bray, Bastian Rieck
Graph Kernels: State-of-the-Art and Future Challenges. Found. Trends Mach. Learn. 13 (5-6) (2020)
Caroline Weis, Max Horn, Bastian Rieck, Aline Cuénod, Adrian Egli, Karsten M. Borgwardt
Topological and kernel-based microbial phenotype prediction from MALDI-TOF mass spectra. Bioinform. 36 (Supplement-1) (2020)
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
Machine learning for early prediction of circulatory failure in the intensive care unit. CoRR (2019)
Mahito Sugiyama, Karsten M. Borgwardt
Finding Statistically Significant Interactions between Continuous Features. IJCAI (2019)
Matteo Togninalli, M. Elisabetta Ghisu, Felipe Llinares-López, Bastian Rieck, Karsten M. Borgwardt
Wasserstein Weisfeiler-Lehman Graph Kernels. CoRR (2019)
Michael Moor, Max Horn, Bastian Rieck, Karsten M. Borgwardt
Topological Autoencoders. CoRR (2019)
Felipe Llinares-López, Laetitia Papaxanthos, Damian Roqueiro, Dean A. Bodenham, Karsten M. Borgwardt
CASMAP: detection of statistically significant combinations of SNPs in association mapping. Bioinform. 35 (15) (2019)
Max Horn, Michael Moor, Christian Bock, Bastian Rieck, Karsten M. Borgwardt
Set Functions for Time Series. CoRR (2019)
Matteo Togninalli, M. Elisabetta Ghisu, Felipe Llinares-López, Bastian Rieck, Karsten M. Borgwardt
Wasserstein Weisfeiler-Lehman Graph Kernels. NeurIPS (2019)
Karsten M. Borgwardt, Po-Ling Loh, Evimaria Terzi, Antti Ukkonen
Introduction to the special issue for the ECML PKDD 2019 journal track. Mach. Learn. 108 (8-9) (2019)
Michael Moor, Max Horn, Bastian Rieck, Damian Roqueiro, Karsten M. Borgwardt
Early Recognition of Sepsis with Gaussian Process Temporal Convolutional Networks and Dynamic Time Warping. MLHC (2019)
Bastian Rieck, Matteo Togninalli, Christian Bock, Michael Moor, Max Horn, Thomas Gumbsch, Karsten M. Borgwardt
Neural Persistence: A Complexity Measure for Deep Neural Networks Using Algebraic Topology. ICLR (Poster) (2019)
Karsten M. Borgwardt, Po-Ling Loh, Evimaria Terzi, Antti Ukkonen
Introduction to the special issue for the ECML PKDD 2019 journal track. Data Min. Knowl. Discov. 33 (5) (2019)
Bastian Rieck, Christian Bock, Karsten M. Borgwardt
A Persistent Weisfeiler-Lehman Procedure for Graph Classification. ICML (2019)
Michael Moor, Max Horn, Bastian Rieck, Damian Roqueiro, Karsten M. Borgwardt
Temporal Convolutional Networks and Dynamic Time Warping can Drastically Improve the Early Prediction of Sepsis. CoRR (2019)
Christian Bock, Matteo Togninalli, M. Elisabetta Ghisu, Thomas Gumbsch, Bastian Rieck, Karsten M. Borgwardt
A Wasserstein Subsequence Kernel for Time Series. ICDM (2019)
Bastian Rieck, Matteo Togninalli, Christian Bock, Michael Moor, Max Horn, Thomas Gumbsch, Karsten M. Borgwardt
Neural Persistence: A Complexity Measure for Deep Neural Networks Using Algebraic Topology. CoRR (2018)
Christian Bock, Thomas Gumbsch, Michael Moor, Bastian Rieck, Damian Roqueiro, Karsten M. Borgwardt
Association mapping in biomedical time series via statistically significant shapelet mining. Bioinform. 34 (13) (2018)
Matteo Togninalli, Damian Roqueiro, COPDGene Investigators, Karsten M. Borgwardt
Accurate and adaptive imputation of summary statistics in mixed-ethnicity cohorts. Bioinform. 34 (17) (2018)
Xiao He, Lukas Folkman, Karsten M. Borgwardt
Kernelized rank learning for personalized drug recommendation. Bioinform. 34 (16) (2018)
Matteo Togninalli, Ümit Seren, Dazhe Meng, Joffrey Fitz, Magnus Nordborg, Detlef Weigel, Karsten M. Borgwardt, Arthur Korte, Dominik G. Grimm
The AraGWAS Catalog: a curated and standardized Arabidopsis thaliana GWAS catalog. Nucleic Acids Res. 46 (Database-Issue) (2018)
Mahito Sugiyama, M. Elisabetta Ghisu, Felipe Llinares-López, Karsten M. Borgwardt
graphkernels: R and Python packages for graph comparison. Bioinform. 34 (3) (2018)
Limin Li, Xiao He, Karsten M. Borgwardt
Multi-target drug repositioning by bipartite block-wise sparse multi-task learning. BMC Syst. Biol. 12 (4) (2018)
Xiao He, Thomas Gumbsch, Damian Roqueiro, Karsten M. Borgwardt
Kernel Conditional Clustering. ICDM (2017)
Xiao He, Limin Li, Damian Roqueiro, Karsten M. Borgwardt
Multi-view Spectral Clustering on Conflicting Views. ECML/PKDD (2) (2017)
Mahito Sugiyama, Karsten M. Borgwardt
Significant Pattern Mining on Continuous Variables. CoRR (2017)
Felipe Llinares-López, Laetitia Papaxanthos, Dean A. Bodenham, Damian Roqueiro, COPDGene Investigators, Karsten M. Borgwardt
Genome-wide genetic heterogeneity discovery with categorical covariates. Bioinform. 33 (12) (2017)
Ümit Seren, Dominik G. Grimm, Joffrey Fitz, Detlef Weigel, Magnus Nordborg, Karsten M. Borgwardt, Arthur Korte
AraPheno: a public database for Arabidopsis thaliana phenotypes. Nucleic Acids Res. 45 (Database-Issue) (2017)
Laetitia Papaxanthos, Felipe Llinares-López, Dean A. Bodenham, Karsten M. Borgwardt
Finding significant combinations of features in the presence of categorical covariates. NIPS (2016)
Felipe Llinares-López, Dominik G. Grimm, Dean A. Bodenham, Udo Gieraths, Mahito Sugiyama, Beth Rowan, Karsten M. Borgwardt
Genome-wide detection of intervals of genetic heterogeneity associated with complex traits. Bioinform. 31 (12) (2015)
Felipe Llinares-López, Laetitia Papaxanthos, Dean A. Bodenham, Karsten M. Borgwardt
Searching for significant patterns in stratified data. CoRR (2015)
Mahito Sugiyama, Karsten M. Borgwardt
Halting in Random Walk Kernels. NIPS (2015)
Damian Roqueiro, Menno J. Witteveen, Verneri Anttila, Gisela M. Terwindt, Arn M. J. M. van den Maagdenberg, Karsten M. Borgwardt
phenotyping via co-training for improved phenotype prediction from genotype. Bioinform. 31 (12) (2015)
Mahito Sugiyama, Felipe Llinares-López, Niklas Kasenburg, Karsten M. Borgwardt
Significant Subgraph Mining with Multiple Testing Correction. SDM (2015)
Felipe Llinares-López, Mahito Sugiyama, Laetitia Papaxanthos, Karsten M. Borgwardt
Fast and Memory-Efficient Significant Pattern Mining via Permutation Testing. KDD (2015)
Mahito Sugiyama, Felipe Llinares-López, Niklas Kasenburg, Karsten M. Borgwardt
Significant Subgraph Mining with Multiple Testing Correction. CoRR (2014)
Mahito Sugiyama, Chloé-Agathe Azencott, Dominik G. Grimm, Yoshinobu Kawahara, Karsten M. Borgwardt
Multi-Task Feature Selection on Multiple Networks via Maximum Flows. SDM (2014)
Felipe Llinares, Mahito Sugiyama, Karsten M. Borgwardt
Identifying Higher-order Combinations of Binary Features. CoRR (2014)
Aasa Feragen, Jens Petersen, Dominik G. Grimm, Asger Dirksen, Jesper Johannes Holst Pedersen, Karsten M. Borgwardt, Marleen de Bruijne
Geometric Tree Kernels: Classification of COPD from Airway Tree Geometry. IPMI (2013)
Aasa Feragen, Niklas Kasenburg, Jens Petersen, Marleen de Bruijne, Karsten M. Borgwardt
Scalable kernels for graphs with continuous attributes. NIPS (2013)
Barbara Rakitsch, Christoph Lippert, Oliver Stegle, Karsten M. Borgwardt
A Lasso multi-marker mixed model for association mapping with population structure correction. Bioinform. 29 (2) (2013)
Chloé-Agathe Azencott, Dominik G. Grimm, Mahito Sugiyama, Yoshinobu Kawahara, Karsten M. Borgwardt
Efficient network-guided multi-locus association mapping with graph cuts. Bioinform. 29 (13) (2013)
Mahito Sugiyama, Karsten M. Borgwardt
Measuring Statistical Dependence via the Mutual Information Dimension. IJCAI (2013)
Nicoló Fusi, Christoph Lippert, Karsten M. Borgwardt, Neil D. Lawrence, Oliver Stegle
Detecting regulatory gene-environment interactions with unmeasured environmental factors. Bioinform. 29 (11) (2013)
Barbara Rakitsch, Christoph Lippert, Karsten M. Borgwardt, Oliver Stegle
It is all in the noise: Efficient multi-task Gaussian process inference with structured residuals. NIPS (2013)
Aasa Feragen, Jens Petersen, Dominik G. Grimm, Asger Dirksen, Jesper Johannes Holst Pedersen, Karsten M. Borgwardt, Marleen de Bruijne
Geometric tree kernels: Classification of COPD from airway tree geometry CoRR (2013)
Mahito Sugiyama, Karsten M. Borgwardt
Rapid Distance-Based Outlier Detection via Sampling. NIPS (2013)
Arthur Gretton, Karsten M. Borgwardt, Malte J. Rasch, Bernhard Schölkopf, Alexander J. Smola
A Kernel Two-Sample Test. J. Mach. Learn. Res. 13 (2012)
Le Song, Alexander J. Smola, Arthur Gretton, Justin Bedo, Karsten M. Borgwardt
Feature Selection via Dependence Maximization. J. Mach. Learn. Res. 13 (2012)
Dominik G. Grimm, Bastian Greshake, Stefan Kleeberger, Christoph Lippert, Oliver Stegle, Bernhard Schölkopf, Detlef Weigel, Karsten M. Borgwardt
easyGWAS: An integrated interspecies platform for performing genome-wide association studies CoRR (2012)
Theofanis Karaletsos, Oliver Stegle, Christine Dreyer, John M. Winn, Karsten M. Borgwardt
ShapePheno: unsupervised extraction of shape phenotypes from biological image collections. Bioinform. 28 (7) (2012)
Panagiotis Achlioptas, Bernhard Schölkopf, Karsten M. Borgwardt
Two-locus association mapping in subquadratic time. KDD (2011)
Nino Shervashidze, Pascal Schweitzer, Erik Jan van Leeuwen, Kurt Mehlhorn, Karsten M. Borgwardt
Weisfeiler-Lehman Graph Kernels. J. Mach. Learn. Res. 12 (2011)
Oliver Stegle, Christoph Lippert, Joris M. Mooij, Neil D. Lawrence, Karsten M. Borgwardt
Efficient inference in matrix-variate Gaussian models with \iid observation noise. NIPS (2011)
Karin Klotzbücher, Yasushi Kobayashi, Nino Shervashidze, Oliver Stegle, Bertram Müller-Myhsok, Detlef Weigel, Karsten M. Borgwardt
Efficient branch-and-bound techniques for two-locus association mapping. BMC Bioinform. 12 (S-11) (2011)
Tony Kam-Thong, Benno Pütz, Nazanin Karbalai, Bertram Müller-Myhsok, Karsten M. Borgwardt
Epistasis detection on quantitative phenotypes by exhaustive enumeration using GPUs. Bioinform. 27 (13) (2011)
Limin Li, Barbara Rakitsch, Karsten M. Borgwardt
ccSVM: correcting Support Vector Machines for confounding factors in biological data classification. Bioinform. 27 (13) (2011)
Hendrik Blockeel, Karsten M. Borgwardt, Luc De Raedt, Pedro M. Domingos, Kristian Kersting, Xifeng Yan
Guest editorial to the special issue on inductive logic programming, mining and learning in graphs and statistical relational learning. Mach. Learn. 83 (2) (2011)
Bianca Wackersreuther, Peter Wackersreuther, Annahita Oswald, Christian Böhm, Karsten M. Borgwardt
Frequent subgraph discovery in dynamic networks. MLG@KDD (2010)
Oliver Stegle, Katherine J. Denby, Emma J. Cooke, David L. Wild, Zoubin Ghahramani, Karsten M. Borgwardt
A Robust Bayesian Two-Sample Test for Detecting Intervals of Differential Gene Expression in Microarray Time Series. J. Comput. Biol. 17 (3) (2010)
Marisa Thoma, Hong Cheng, Arthur Gretton, Jiawei Han, Hans-Peter Kriegel, Alexander J. Smola, Le Song, Philip S. Yu, Xifeng Yan, Karsten M. Borgwardt
Discriminative frequent subgraph mining with optimality guarantees. Stat. Anal. Data Min. 3 (5) (2010)
Christoph Lippert, Zoubin Ghahramani, Karsten M. Borgwardt
Gene function prediction from synthetic lethality networks via ranking on demand. Bioinform. 26 (7) (2010)
Gustavo Camps-Valls, Nino Shervashidze, Karsten M. Borgwardt
Spatio-Spectral Remote Sensing Image Classification With Graph Kernels. IEEE Geosci. Remote. Sens. Lett. 7 (4) (2010)
S. V. N. Vishwanathan, Nicol N. Schraudolph, Risi Kondor, Karsten M. Borgwardt
Graph Kernels. J. Mach. Learn. Res. 11 (2010)

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Publication Activity (10 Years)

Top Topics

Top Venues

Karsten M. Borgwardt