Karsten M. Borgwardt

159 papers A* 30A 6B 4Misc 2Journal 87Unranked 25

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Conformal Prediction with Knowledge Graphs for Reliable Antimicrobial Resistance Detection with MALDI-TOF Mass Spectra. J. Comput. Biol. Nina Corvelo Benz, Lucas Miranda, Dexiong Chen, Janko Sattler, Karsten M. Borgwardt
2026	J	`jnl`	Fast Graph Generation via Autoregressive Noisy Filtration Modeling. Trans. Mach. Learn. Res. Markus Krimmel, Jenna Wiens, Karsten M. Borgwardt, Dexiong Chen
2025	J	`jnl`	A Comprehensive Benchmark for RNA 3D Structure-Function Modeling. CoRR Luis Wyss, Vincent Mallet, Wissam Karroucha, Karsten M. Borgwardt, Carlos G. Oliver
2025	B	`conf`	Detecting Antimicrobial Resistance Through MALDI-TOF Mass Spectrometry with Statistical Guarantees Using Conformal Prediction. RECOMB Nina Corvelo Benz, Lucas Miranda, Dexiong Chen, Janko Sattler, Karsten M. Borgwardt
2025	J	`jnl`	Endowing protein language models with structural knowledge. Bioinform. Philip Hartout, Dexiong Chen, Paolo Pellizzoni, Carlos G. Oliver, Karsten M. Borgwardt
2025	J	`jnl`	Flatten Graphs as Sequences: Transformers are Scalable Graph Generators. CoRR Dexiong Chen, Markus Krimmel, Karsten M. Borgwardt
2025	A*	`conf`	Graph Neural Networks Can (Often) Count Substructures. ICLR Paolo Pellizzoni, Till Hendrik Schulz, Karsten M. Borgwardt
2025	J	`jnl`	ISMB/ECCB 2025 Proceedings. Bioinform. Karsten M. Borgwardt, Tijana Milenkovic
2025	A*	`conf`	Learning Long Range Dependencies on Graphs via Random Walks. ICLR Dexiong Chen, Till Hendrik Schulz, Karsten M. Borgwardt
2025	J	`jnl`	PolyGraph Discrepancy: a classifier-based metric for graph generation. CoRR Markus Krimmel, Philip Hartout, Karsten M. Borgwardt, Dexiong Chen
2025	J	`jnl`	Refine Drugs, Don't Complete Them: Uniform-Source Discrete Flows for Fragment-Based Drug Discovery. CoRR Benno Kaech, Luis Wyss, Karsten M. Borgwardt, Gianvito Grasso
2025	J	`jnl`	Towards Fast Graph Generation via Autoregressive Noisy Filtration Modeling. CoRR Markus Krimmel, Jenna Wiens, Karsten M. Borgwardt, Dexiong Chen
2024	J	`jnl`	An empirical study on KDIGO-defined acute kidney injury prediction in the intensive care unit. Bioinform. Xinrui Lyu, Bowen Fan, Matthias Hüser, Philip Hartout, Thomas Gumbsch, Martin Faltys, Tobias M. Merz, Gunnar Rätsch, Karsten M. Borgwardt
2024	J	`jnl`	Biomarker identification by interpretable maximum mean discrepancy. Bioinform. Michael F. Adamer, Sarah C. Brüningk, Dexiong Chen, Karsten M. Borgwardt
2024	J	`jnl`	Endowing Protein Language Models with Structural Knowledge. CoRR Dexiong Chen, Philip Hartout, Paolo Pellizzoni, Carlos G. Oliver, Karsten M. Borgwardt
2024	J	`jnl`	Learning Long Range Dependencies on Graphs via Random Walks. CoRR Dexiong Chen, Till Hendrik Schulz, Karsten M. Borgwardt
2024	A*	`conf`	On the Expressivity and Sample Complexity of Node-Individualized Graph Neural Networks. NeurIPS Paolo Pellizzoni, Till Hendrik Schulz, Dexiong Chen, Karsten M. Borgwardt
2024	B	`conf`	Structure- and Function-Aware Substitution Matrices via Learnable Graph Matching. RECOMB Paolo Pellizzoni, Carlos G. Oliver, Karsten M. Borgwardt
2023	J	`jnl`	<tt>networkGWAS</tt> : a network-based approach to discover genetic associations. Bioinform. Giulia Muzio, Leslie O'Bray, Laetitia Meng-Papaxanthos, Juliane Klatt, Krista Fischer, Karsten M. Borgwardt
2023	A*	`conf`	FASM and FAST-YB: Significant Pattern Mining with False Discovery Rate Control. ICDM Paolo Pellizzoni, Karsten M. Borgwardt
2023	A*	`conf`	Fisher Information Embedding for Node and Graph Learning. ICML Dexiong Chen, Paolo Pellizzoni, Karsten M. Borgwardt
2023	J	`jnl`	Fisher Information Embedding for Node and Graph Learning. CoRR Dexiong Chen, Paolo Pellizzoni, Karsten M. Borgwardt
2023	J	`jnl`	Higher-order genetic interaction discovery with network-based biological priors. Bioinform. Paolo Pellizzoni, Giulia Muzio, Karsten M. Borgwardt
2023	J	`jnl`	Multi-modal deep learning improves grain yield prediction in wheat breeding by fusing genomics and phenomics. Bioinform. Matteo Togninalli, Xu Wang, Tim Kucera, Sandesh Shrestha, Philomin Juliana, Suchismita Mondal, Francisco Pinto Espinosa, Velu Govindan, Leonardo Crespo-Herrera, Julio Huerta-Espino, Ravi P. Singh, Karsten M. Borgwardt, Jesse Poland
2023	J	`jnl`	Multimodal learning in clinical proteomics: enhancing antimicrobial resistance prediction models with chemical information. Bioinform. Giovanni Visonà, Diane Duroux, Lucas Miranda, Emese Sükei, Yiran Li, Karsten M. Borgwardt, Carlos G. Oliver
2023	A*	`conf`	ProteinShake: Building datasets and benchmarks for deep learning on protein structures. NeurIPS Tim Kucera, Carlos G. Oliver, Dexiong Chen, Karsten M. Borgwardt
2023	J	`jnl`	SIMBSIG: similarity search and clustering for biobank-scale data. Bioinform. Michael F. Adamer, Eljas Roellin, Lucie Bourguignon, Karsten M. Borgwardt
2023	A*	`conf`	Unsupervised Manifold Alignment with Joint Multidimensional Scaling. ICLR Dexiong Chen, Bowen Fan, Carlos G. Oliver, Karsten M. Borgwardt
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
2022	J	`jnl`	Approximate Network Motif Mining Via Graph Learning. CoRR Carlos G. Oliver, Dexiong Chen, Vincent Mallet, Pericles Philippopoulos, Karsten M. Borgwardt
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	—	`ch.`	Machine Learning in Medicine. Mach. Learn. under Resour. Constraints Vol. 3 (3) Catherine R. Jutzeler, Karsten M. Borgwardt
2022	J	`jnl`	Prediction of recovery from multiple organ dysfunction syndrome in pediatric sepsis patients. Bioinform. Bowen Fan, Juliane Klatt, Michael Moor, Latasha A. Daniels, Philipp K. A Agyeman, Christoph Berger, Eric Giannoni, Martin Stocker, Klara M. Posfay-Barbe, Ulrich Heininger, Sara Bernhard-Stirnemann, Anita Niederer-Loher, Christian R. Kahlert, Giancarlo Natalucci, Christa Relly, Thomas Riedel, Christoph Aebi, Luregn J. Schlapbach, Lazaro N. Sanchez-Pinto, Karsten M. Borgwardt
2022	A*	`conf`	Structure-Aware Transformer for Graph Representation Learning. ICML Dexiong Chen, Leslie O'Bray, Karsten M. Borgwardt
2022	J	`jnl`	Structure-Aware Transformer for Graph Representation Learning. CoRR Dexiong Chen, Leslie O'Bray, Karsten M. Borgwardt
2022	A*	`conf`	Topological Graph Neural Networks. ICLR Max Horn, Edward De Brouwer, Michael Moor, Yves Moreau, Bastian Rieck, Karsten M. Borgwardt
2022	J	`jnl`	Unsupervised Manifold Alignment with Joint Multidimensional Scaling. CoRR Dexiong Chen, Bowen Fan, Carlos G. Oliver, Karsten M. Borgwardt
2021	J	`jnl`	Biological network analysis with deep learning. Briefings Bioinform. Giulia Muzio, Leslie O'Bray, Karsten M. Borgwardt
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	—	`ch.`	Machine Learning for Biomedical Time Series Classification: From Shapelets to Deep Learning. Artificial Neural Networks, 3rd Edition Christian Bock, Michael Moor, Catherine R. Jutzeler, Karsten M. Borgwardt
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`	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`	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`	AraPheno and the AraGWAS Catalog 2020: a major database update including RNA-Seq and knockout mutation data for Nucleic Acids Res. Matteo Togninalli, Ümit Seren, Jan A. Freudenthal, J. Grey Monroe, Dazhe Meng, Magnus Nordborg, Detlef Weigel, Karsten M. Borgwardt, Arthur Korte, Dominik G. Grimm
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	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`	Kernel conditional clustering and kernel conditional semi-supervised learning. Knowl. Inf. Syst. Xiao He, Thomas Gumbsch, Damian Roqueiro, Karsten M. Borgwardt
2020	J	`jnl`	Path Imputation Strategies for Signature Models. CoRR Michael Moor, Max Horn, Christian Bock, Karsten M. Borgwardt, Bastian Rieck
2020	J	`jnl`	Prediction of cancer driver genes through network-based moment propagation of mutation scores. Bioinform. Anja C. Gumpinger, Kasper Lage, Heiko Horn, Karsten M. Borgwardt
2020	—	`conf`	SPHN/PHRT: Forming a Swiss-Wide Infrastructure for Data-Driven Sepsis Research. MIE 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
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 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	J	`jnl`	CASMAP: detection of statistically significant combinations of SNPs in association mapping. Bioinform. Felipe Llinares-López, Laetitia Papaxanthos, Damian Roqueiro, Dean A. Bodenham, 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	A*	`conf`	Finding Statistically Significant Interactions between Continuous Features. IJCAI Mahito Sugiyama, Karsten M. Borgwardt
2019	J	`jnl`	Introduction to the special issue for the ECML PKDD 2019 journal track. Data Min. Knowl. Discov. Karsten M. Borgwardt, Po-Ling Loh, Evimaria Terzi, Antti Ukkonen
2019	J	`jnl`	Introduction to the special issue for the ECML PKDD 2019 journal track. Mach. Learn. Karsten M. Borgwardt, Po-Ling Loh, Evimaria Terzi, Antti Ukkonen
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`	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	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`	Accurate and adaptive imputation of summary statistics in mixed-ethnicity cohorts. Bioinform. Matteo Togninalli, Damian Roqueiro, COPDGene Investigators, 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`	Kernelized rank learning for personalized drug recommendation. Bioinform. Xiao He, Lukas Folkman, Karsten M. Borgwardt
2018	J	`jnl`	Multi-target drug repositioning by bipartite block-wise sparse multi-task learning. BMC Syst. Biol. Limin Li, Xiao He, Karsten M. Borgwardt
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`	The AraGWAS Catalog: a curated and standardized Arabidopsis thaliana GWAS catalog. Nucleic Acids Res. Matteo Togninalli, Ümit Seren, Dazhe Meng, Joffrey Fitz, Magnus Nordborg, Detlef Weigel, Karsten M. Borgwardt, Arthur Korte, Dominik G. Grimm
2018	J	`jnl`	graphkernels: R and Python packages for graph comparison. Bioinform. Mahito Sugiyama, M. Elisabetta Ghisu, Felipe Llinares-López, Karsten M. Borgwardt
2017	J	`jnl`	AraPheno: a public database for Arabidopsis thaliana phenotypes. Nucleic Acids Res. Ümit Seren, Dominik G. Grimm, Joffrey Fitz, Detlef Weigel, Magnus Nordborg, Karsten M. Borgwardt, Arthur Korte
2017	J	`jnl`	Genome-wide genetic heterogeneity discovery with categorical covariates. Bioinform. Felipe Llinares-López, Laetitia Papaxanthos, Dean A. Bodenham, Damian Roqueiro, COPDGene Investigators, Karsten M. Borgwardt
2017	A*	`conf`	Kernel Conditional Clustering. ICDM Xiao He, Thomas Gumbsch, Damian Roqueiro, Karsten M. Borgwardt
2017	—	`conf`	Multi-view Spectral Clustering on Conflicting Views. ECML/PKDD (2) Xiao He, Limin Li, Damian Roqueiro, Karsten M. Borgwardt
2017	J	`jnl`	Significant Pattern Mining on Continuous Variables. CoRR Mahito Sugiyama, Karsten M. Borgwardt
2016	—	`conf`	Finding significant combinations of features in the presence of categorical covariates. NIPS Laetitia Papaxanthos, Felipe Llinares-López, Dean A. Bodenham, Karsten M. Borgwardt
2015	A*	`conf`	Fast and Memory-Efficient Significant Pattern Mining via Permutation Testing. KDD Felipe Llinares-López, Mahito Sugiyama, Laetitia Papaxanthos, Karsten M. Borgwardt
2015	J	`jnl`	Genome-wide detection of intervals of genetic heterogeneity associated with complex traits. Bioinform. Felipe Llinares-López, Dominik G. Grimm, Dean A. Bodenham, Udo Gieraths, Mahito Sugiyama, Beth Rowan, Karsten M. Borgwardt
2015	—	`conf`	Halting in Random Walk Kernels. NIPS Mahito Sugiyama, Karsten M. Borgwardt
2015	J	`jnl`	Searching for significant patterns in stratified data. CoRR Felipe Llinares-López, Laetitia Papaxanthos, Dean A. Bodenham, Karsten M. Borgwardt
2015	A	`conf`	Significant Subgraph Mining with Multiple Testing Correction. SDM Mahito Sugiyama, Felipe Llinares-López, Niklas Kasenburg, Karsten M. Borgwardt
2014	J	`jnl`	Identifying Higher-order Combinations of Binary Features. CoRR Felipe Llinares, Mahito Sugiyama, Karsten M. Borgwardt
2014	A	`conf`	Multi-Task Feature Selection on Multiple Networks via Maximum Flows. SDM Mahito Sugiyama, Chloé-Agathe Azencott, Dominik G. Grimm, Yoshinobu Kawahara, Karsten M. Borgwardt
2014	J	`jnl`	Significant Subgraph Mining with Multiple Testing Correction. CoRR Mahito Sugiyama, Felipe Llinares-López, Niklas Kasenburg, Karsten M. Borgwardt
2013	J	`jnl`	A Lasso multi-marker mixed model for association mapping with population structure correction. Bioinform. Barbara Rakitsch, Christoph Lippert, Oliver Stegle, Karsten M. Borgwardt
2013	J	`jnl`	Detecting regulatory gene-environment interactions with unmeasured environmental factors. Bioinform. Nicoló Fusi, Christoph Lippert, Karsten M. Borgwardt, Neil D. Lawrence, Oliver Stegle
2013	J	`jnl`	Efficient network-guided multi-locus association mapping with graph cuts. Bioinform. Chloé-Agathe Azencott, Dominik G. Grimm, Mahito Sugiyama, Yoshinobu Kawahara, Karsten M. Borgwardt
2013	—	`conf`	Geometric Tree Kernels: Classification of COPD from Airway Tree Geometry. IPMI Aasa Feragen, Jens Petersen, Dominik G. Grimm, Asger Dirksen, Jesper Johannes Holst Pedersen, Karsten M. Borgwardt, Marleen de Bruijne
2013	J	`jnl`	Geometric tree kernels: Classification of COPD from airway tree geometry CoRR Aasa Feragen, Jens Petersen, Dominik G. Grimm, Asger Dirksen, Jesper Johannes Holst Pedersen, Karsten M. Borgwardt, Marleen de Bruijne
2013	—	`conf`	It is all in the noise: Efficient multi-task Gaussian process inference with structured residuals. NIPS Barbara Rakitsch, Christoph Lippert, Karsten M. Borgwardt, Oliver Stegle
2013	A*	`conf`	Measuring Statistical Dependence via the Mutual Information Dimension. IJCAI Mahito Sugiyama, Karsten M. Borgwardt
2013	—	`conf`	Rapid Distance-Based Outlier Detection via Sampling. NIPS Mahito Sugiyama, Karsten M. Borgwardt
2013	—	`conf`	Scalable kernels for graphs with continuous attributes. NIPS Aasa Feragen, Niklas Kasenburg, Jens Petersen, Marleen de Bruijne, Karsten M. Borgwardt
2012	J	`jnl`	A Kernel Two-Sample Test. J. Mach. Learn. Res. Arthur Gretton, Karsten M. Borgwardt, Malte J. Rasch, Bernhard Schölkopf, Alexander J. Smola
2012	J	`jnl`	Feature Selection via Dependence Maximization. J. Mach. Learn. Res. Le Song, Alexander J. Smola, Arthur Gretton, Justin Bedo, Karsten M. Borgwardt
2012	J	`jnl`	ShapePheno: unsupervised extraction of shape phenotypes from biological image collections. Bioinform. Theofanis Karaletsos, Oliver Stegle, Christine Dreyer, John M. Winn, Karsten M. Borgwardt
2012	J	`jnl`	easyGWAS: An integrated interspecies platform for performing genome-wide association studies CoRR Dominik G. Grimm, Bastian Greshake, Stefan Kleeberger, Christoph Lippert, Oliver Stegle, Bernhard Schölkopf, Detlef Weigel, Karsten M. Borgwardt
2011	J	`jnl`	Efficient branch-and-bound techniques for two-locus association mapping. BMC Bioinform. Karin Klotzbücher, Yasushi Kobayashi, Nino Shervashidze, Oliver Stegle, Bertram Müller-Myhsok, Detlef Weigel, Karsten M. Borgwardt
2011	—	`conf`	Efficient inference in matrix-variate Gaussian models with \iid observation noise. NIPS Oliver Stegle, Christoph Lippert, Joris M. Mooij, Neil D. Lawrence, Karsten M. Borgwardt
2011	J	`jnl`	Epistasis detection on quantitative phenotypes by exhaustive enumeration using GPUs. Bioinform. Tony Kam-Thong, Benno Pütz, Nazanin Karbalai, Bertram Müller-Myhsok, Karsten M. Borgwardt
2011	J	`jnl`	Guest editorial to the special issue on inductive logic programming, mining and learning in graphs and statistical relational learning. Mach. Learn. Hendrik Blockeel, Karsten M. Borgwardt, Luc De Raedt, Pedro M. Domingos, Kristian Kersting, Xifeng Yan
2011	—	`ch.`	Kernel Methods in Bioinformatics. Handbook of Statistical Bioinformatics Karsten M. Borgwardt
2011	A*	`conf`	Two-locus association mapping in subquadratic time. KDD Panagiotis Achlioptas, Bernhard Schölkopf, Karsten M. Borgwardt
2011	J	`jnl`	Weisfeiler-Lehman Graph Kernels. J. Mach. Learn. Res. Nino Shervashidze, Pascal Schweitzer, Erik Jan van Leeuwen, Kurt Mehlhorn, Karsten M. Borgwardt
2011	J	`jnl`	ccSVM: correcting Support Vector Machines for confounding factors in biological data classification. Bioinform. Limin Li, Barbara Rakitsch, Karsten M. Borgwardt
2010	J	`jnl`	A Robust Bayesian Two-Sample Test for Detecting Intervals of Differential Gene Expression in Microarray Time Series. J. Comput. Biol. Oliver Stegle, Katherine J. Denby, Emma J. Cooke, David L. Wild, Zoubin Ghahramani, Karsten M. Borgwardt
2010	J	`jnl`	Discriminative frequent subgraph mining with optimality guarantees. Stat. Anal. Data Min. Marisa Thoma, Hong Cheng, Arthur Gretton, Jiawei Han, Hans-Peter Kriegel, Alexander J. Smola, Le Song, Philip S. Yu, Xifeng Yan, Karsten M. Borgwardt
2010	—	`conf`	Frequent subgraph discovery in dynamic networks. MLG@KDD Bianca Wackersreuther, Peter Wackersreuther, Annahita Oswald, Christian Böhm, Karsten M. Borgwardt
2010	J	`jnl`	Gene function prediction from synthetic lethality networks via ranking on demand. Bioinform. Christoph Lippert, Zoubin Ghahramani, Karsten M. Borgwardt
2010	J	`jnl`	Graph Kernels. J. Mach. Learn. Res. S. V. N. Vishwanathan, Nicol N. Schraudolph, Risi Kondor, Karsten M. Borgwardt
2010	J	`jnl`	Spatio-Spectral Remote Sensing Image Classification With Graph Kernels. IEEE Geosci. Remote. Sens. Lett. Gustavo Camps-Valls, Nino Shervashidze, Karsten M. Borgwardt
2009	B	`conf`	A Robust Bayesian Two-Sample Test for Detecting Intervals of Differential Gene Expression in Microarray Time Series. RECOMB Oliver Stegle, Katherine J. Denby, David L. Wild, Zoubin Ghahramani, Karsten M. Borgwardt
2009	A	`conf`	A kernel method for unsupervised structured network inference. AISTATS Christoph Lippert, Oliver Stegle, Zoubin Ghahramani, Karsten M. Borgwardt
2009	J	`jnl`	Bayesian two-sample tests CoRR Karsten M. Borgwardt, Zoubin Ghahramani
2009	—	`conf`	Discovering Temporal Patterns of Differential Gene Expression in Microarray Time Series. GCB Oliver Stegle, Katherine J. Denby, David L. Wild, Stuart McHattie, Andrew Meade, Zoubin Ghahramani, Karsten M. Borgwardt
2009	A	`conf`	Efficient graphlet kernels for large graph comparison. AISTATS Nino Shervashidze, S. V. N. Vishwanathan, Tobias Petri, Kurt Mehlhorn, Karsten M. Borgwardt
2009	—	`conf`	Fast subtree kernels on graphs. NIPS Nino Shervashidze, Karsten M. Borgwardt
2009	A	`conf`	Near-optimal Supervised Feature Selection among Frequent Subgraphs. SDM Marisa Thoma, Hong Cheng, Arthur Gretton, Jiawei Han, Hans-Peter Kriegel, Alexander J. Smola, Le Song, Philip S. Yu, Xifeng Yan, Karsten M. Borgwardt
2009	—	`ed.`	Proceedings of the Joint 7th Workshop on Mining and Learning with Graphs and the 6th International Workshop on Statistical Relational Learning, MLG/SRL@ILP 2009, Leuven, Belgium, July 2-4, 2009 MLG/SRL@ILP Hendrik Blockeel, Karsten M. Borgwardt, Luc De Raedt, Pedro M. Domingos, Kristian Kersting, Xifeng Yan
2009	A*	`conf`	The graphlet spectrum. ICML Risi Kondor, Nino Shervashidze, Karsten M. Borgwardt
2008	J	`jnl`	A Kernel Method for the Two-Sample Problem CoRR Arthur Gretton, Karsten M. Borgwardt, Malte J. Rasch, Bernhard Schölkopf, Alexander J. Smola
2008	—	`conf`	Combining near-optimal feature selection with gSpan. MLG@ICML Karsten M. Borgwardt, Xifeng Yan, Marisa Thoma, Hong Cheng, Arthur Gretton, Le Song, Alex Smola, Jiawei Han, Philip S. Yu, Hans-Peter Kriegel
2008	J	`jnl`	Graph Kernels CoRR S. V. N. Vishwanathan, Karsten M. Borgwardt, Imre Risi Kondor, Nicol N. Schraudolph
2008	A*	`conf`	Metropolis Algorithms for Representative Subgraph Sampling. ICDM Christian Hübler, Hans-Peter Kriegel, Karsten M. Borgwardt, Zoubin Ghahramani
2008	—	`conf`	Representative Subgraph Sampling using Markov Chain Monte Carlo Methods. MLG@ICML Christian Hübler, Karsten M. Borgwardt, Hans-Peter Kriegel, Zoubin Ghahramani
2008	A*	`conf`	The skew spectrum of graphs. ICML Risi Kondor, Karsten M. Borgwardt
2007	A*	`conf`	A Kernel Approach to Comparing Distributions. AAAI Arthur Gretton, Karsten M. Borgwardt, Malte J. Rasch, Bernhard Schölkopf, Alexander J. Smola
2007	A*	`conf`	A dependence maximization view of clustering. ICML Le Song, Alexander J. Smola, Arthur Gretton, Karsten M. Borgwardt
2007	—	`conf`	An Efficient Sampling Scheme For Comparison of Large Graphs. MLG Karsten M. Borgwardt, Tobias Petri, S. V. N. Vishwanathan, Hans-Peter Kriegel
2007	—	`conf`	Colored Maximum Variance Unfolding. NIPS Le Song, Alexander J. Smola, Karsten M. Borgwardt, Arthur Gretton
2007	J	`jnl`	Future trends in data mining. Data Min. Knowl. Discov. Hans-Peter Kriegel, Karsten M. Borgwardt, Peer Kröger, Alexey Pryakhin, Matthias Schubert, Arthur Zimek
2007	—	`conf`	Gene selection via the BAHSIC family of algorithms. ISMB/ECCB (Supplement of Bioinformatics) Le Song, Justin Bedo, Karsten M. Borgwardt, Arthur Gretton, Alexander J. Smola
2007	Misc	`conf`	Graph Kernels For Disease Outcome Prediction From Protein-Protein Interaction Networks. Pacific Symposium on Biocomputing Karsten M. Borgwardt, Hans-Peter Kriegel
2007	—	`ch.`	Graph-Kerne [Graph Kernels]. Ausgezeichnete Informatikdissertationen Karsten M. Borgwardt
2007	J	`jnl`	Supervised Feature Selection via Dependence Estimation CoRR Le Song, Alexander J. Smola, Arthur Gretton, Karsten M. Borgwardt, Justin Bedo
2007	A*	`conf`	Supervised feature selection via dependence estimation. ICML Le Song, Alexander J. Smola, Arthur Gretton, Karsten M. Borgwardt, Justin Bedo
2006	A	`conf`	3DString: a feature string kernel for 3D object classification on voxelized data. CIKM Johannes Aßfalg, Karsten M. Borgwardt, Hans-Peter Kriegel
2006	—	`conf`	A Kernel Method for the Two-Sample-Problem. NIPS Arthur Gretton, Karsten M. Borgwardt, Malte J. Rasch, Bernhard Schölkopf, Alexander J. Smola
2006	Misc	`conf`	Class Prediction from Time Series Gene Expression Profiles Using Dynamical Systems Kernels. Pacific Symposium on Biocomputing Karsten M. Borgwardt, S. V. N. Vishwanathan, Hans-Peter Kriegel
2006	—	`conf`	Correcting Sample Selection Bias by Unlabeled Data. NIPS Jiayuan Huang, Alexander J. Smola, Arthur Gretton, Karsten M. Borgwardt, Bernhard Schölkopf
2006	—	`conf`	Fast Computation of Graph Kernels. NIPS S. V. N. Vishwanathan, Karsten M. Borgwardt, Nicol N. Schraudolph
2006	—	`conf`	Integrating structured biological data by Kernel Maximum Mean Discrepancy. ISMB (Supplement of Bioinformatics) Karsten M. Borgwardt, Arthur Gretton, Malte J. Rasch, Hans-Peter Kriegel, Bernhard Schölkopf, Alexander J. Smola
2006	J	`jnl`	Kernel extrapolation. Neurocomputing S. V. N. Vishwanathan, Karsten M. Borgwardt, Omri Guttman, Alexander J. Smola
2006	A*	`conf`	Pattern Mining in Frequent Dynamic Subgraphs. ICDM Karsten M. Borgwardt, Hans-Peter Kriegel, Peter Wackersreuther
2006	—	`conf`	VGM: visual graph mining. SIGMOD Conference Karsten M. Borgwardt, Sebastian Böttger, Hans-Peter Kriegel
2005	B	`conf`	Joint Regularization. ESANN Karsten M. Borgwardt, Omri Guttman, S. V. N. Vishwanathan, Alexander J. Smola
2005	—	`conf`	Protein function prediction via graph kernels. ISMB (Supplement of Bioinformatics) Karsten M. Borgwardt, Cheng Soon Ong, Stefan Schönauer, S. V. N. Vishwanathan, Alexander J. Smola, Hans-Peter Kriegel
2005	A*	`conf`	Shortest-Path Kernels on Graphs. ICDM Karsten M. Borgwardt, Hans-Peter Kriegel