Karsten M. Borgwardt

Orcid: 0000-0001-7221-2393

Affiliations:
  • Max Planck Institute of Biochemistry, Munich, Germany
  • ETH Zurich, Department of Biosystems Science and Engineering (former)


According to our database1, Karsten M. Borgwardt authored at least 121 papers between 2005 and 2024.

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Bibliography

2024
Learning Long Range Dependencies on Graphs via Random Walks.
CoRR, 2024

Endowing Protein Language Models with Structural Knowledge.
CoRR, 2024

Structure- and Function-Aware Substitution Matrices via Learnable Graph Matching.
Proceedings of the Research in Computational Molecular Biology, 2024

2023
Multimodal learning in clinical proteomics: enhancing antimicrobial resistance prediction models with chemical information.
Bioinform., December, 2023

SIMBSIG: similarity search and clustering for biobank-scale data.
Bioinform., January, 2023

Weisfeiler and Leman go Machine Learning: The Story so far.
J. Mach. Learn. Res., 2023

Higher-order genetic interaction discovery with network-based biological priors.
Bioinform., 2023

ProteinShake: Building datasets and benchmarks for deep learning on protein structures.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Fisher Information Embedding for Node and Graph Learning.
Proceedings of the International Conference on Machine Learning, 2023

Unsupervised Manifold Alignment with Joint Multidimensional Scaling.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

FASM and FAST-YB: Significant Pattern Mining with False Discovery Rate Control.
Proceedings of the IEEE International Conference on Data Mining, 2023

2022
Approximate Network Motif Mining Via Graph Learning.
CoRR, 2022

Structure-Aware Transformer for Graph Representation Learning.
Proceedings of the International Conference on Machine Learning, 2022

Evaluation Metrics for Graph Generative Models: Problems, Pitfalls, and Practical Solutions.
Proceedings of the Tenth International Conference on Learning Representations, 2022

Topological Graph Neural Networks.
Proceedings of the Tenth International Conference on Learning Representations, 2022

Machine Learning in Medicine.
Proceedings of the Machine Learning under Resource Constraints - Volume 3: Applications, 2022

2021
The magnitude vector of images.
CoRR, 2021

Predicting sepsis in multi-site, multi-national intensive care cohorts using deep learning.
CoRR, 2021

Network-guided search for genetic heterogeneity between gene pairs.
Bioinform., 2021

Biological network analysis with deep learning.
Briefings Bioinform., 2021

Filtration Curves for Graph Representation.
Proceedings of the KDD '21: The 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2021

Machine Learning for Biomedical Time Series Classification: From Shapelets to Deep Learning.
Proceedings of the Artificial Neural Networks - Third Edition., 2021

2020
AraPheno and the AraGWAS Catalog 2020: a major database update including RNA-Seq and knockout mutation data for <i>Arabidopsis thaliana</i>.
Nucleic Acids Res., 2020

Kernel conditional clustering and kernel conditional semi-supervised learning.
Knowl. Inf. Syst., 2020

Graph Kernels: State-of-the-Art and Future Challenges.
Found. Trends Mach. Learn., 2020

Accelerating COVID-19 Differential Diagnosis with Explainable Ultrasound Image Analysis.
CoRR, 2020

Path Imputation Strategies for Signature Models.
CoRR, 2020

Topological and kernel-based microbial phenotype prediction from MALDI-TOF mass spectra.
Bioinform., 2020

Prediction of cancer driver genes through network-based moment propagation of mutation scores.
Bioinform., 2020

Uncovering the Topology of Time-Varying fMRI Data using Cubical Persistence.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

SPHN/PHRT: Forming a Swiss-Wide Infrastructure for Data-Driven Sepsis Research.
Proceedings of the Digital Personalized Health and Medicine - Proceedings of MIE 2020, Medical Informatics Europe, Geneva, Switzerland, April 28, 2020

Topological Autoencoders.
Proceedings of the 37th International Conference on Machine Learning, 2020

Set Functions for Time Series.
Proceedings of the 37th International Conference on Machine Learning, 2020

2019
Introduction to the special issue for the ECML PKDD 2019 journal track.
Mach. Learn., 2019

Machine learning for early prediction of circulatory failure in the intensive care unit.
CoRR, 2019

Temporal Convolutional Networks and Dynamic Time Warping can Drastically Improve the Early Prediction of Sepsis.
CoRR, 2019

CASMAP: detection of statistically significant combinations of SNPs in association mapping.
Bioinform., 2019

Wasserstein Weisfeiler-Lehman Graph Kernels.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Early Recognition of Sepsis with Gaussian Process Temporal Convolutional Networks and Dynamic Time Warping.
Proceedings of the Machine Learning for Healthcare Conference, 2019

Finding Statistically Significant Interactions between Continuous Features.
Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019

A Persistent Weisfeiler-Lehman Procedure for Graph Classification.
Proceedings of the 36th International Conference on Machine Learning, 2019

Neural Persistence: A Complexity Measure for Deep Neural Networks Using Algebraic Topology.
Proceedings of the 7th International Conference on Learning Representations, 2019

A Wasserstein Subsequence Kernel for Time Series.
Proceedings of the 2019 IEEE International Conference on Data Mining, 2019

2018
The AraGWAS Catalog: a curated and standardized Arabidopsis thaliana GWAS catalog.
Nucleic Acids Res., 2018

Multi-target drug repositioning by bipartite block-wise sparse multi-task learning.
BMC Syst. Biol., 2018

Accurate and adaptive imputation of summary statistics in mixed-ethnicity cohorts.
Bioinform., 2018

graphkernels: R and Python packages for graph comparison.
Bioinform., 2018

Kernelized rank learning for personalized drug recommendation.
Bioinform., 2018

Association mapping in biomedical time series via statistically significant shapelet mining.
Bioinform., 2018

2017
AraPheno: a public database for Arabidopsis thaliana phenotypes.
Nucleic Acids Res., 2017

Significant Pattern Mining on Continuous Variables.
CoRR, 2017

Genome-wide genetic heterogeneity discovery with categorical covariates.
Bioinform., 2017

Multi-view Spectral Clustering on Conflicting Views.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2017

Kernel Conditional Clustering.
Proceedings of the 2017 IEEE International Conference on Data Mining, 2017

2016
Finding significant combinations of features in the presence of categorical covariates.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

2015
Searching for significant patterns in stratified data.
CoRR, 2015

<i>In silico</i> phenotyping via co-training for improved phenotype prediction from genotype.
Bioinform., 2015

Genome-wide detection of intervals of genetic heterogeneity associated with complex traits.
Bioinform., 2015

Significant Subgraph Mining with Multiple Testing Correction.
Proceedings of the 2015 SIAM International Conference on Data Mining, Vancouver, BC, Canada, April 30, 2015

Halting in Random Walk Kernels.
Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

Fast and Memory-Efficient Significant Pattern Mining via Permutation Testing.
Proceedings of the 21th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2015

2014
Identifying Higher-order Combinations of Binary Features.
CoRR, 2014

Multi-Task Feature Selection on Multiple Networks via Maximum Flows.
Proceedings of the 2014 SIAM International Conference on Data Mining, 2014

2013
A Lasso multi-marker mixed model for association mapping with population structure correction.
Bioinform., 2013

Detecting regulatory gene-environment interactions with unmeasured environmental factors.
Bioinform., 2013

Efficient network-guided multi-locus association mapping with graph cuts.
Bioinform., 2013

Rapid Distance-Based Outlier Detection via Sampling.
Proceedings of the Advances in Neural Information Processing Systems 26: 27th Annual Conference on Neural Information Processing Systems 2013. Proceedings of a meeting held December 5-8, 2013

It is all in the noise: Efficient multi-task Gaussian process inference with structured residuals.
Proceedings of the Advances in Neural Information Processing Systems 26: 27th Annual Conference on Neural Information Processing Systems 2013. Proceedings of a meeting held December 5-8, 2013

Scalable kernels for graphs with continuous attributes.
Proceedings of the Advances in Neural Information Processing Systems 26: 27th Annual Conference on Neural Information Processing Systems 2013. Proceedings of a meeting held December 5-8, 2013

Geometric Tree Kernels: Classification of COPD from Airway Tree Geometry.
Proceedings of the Information Processing in Medical Imaging, 2013

Measuring Statistical Dependence via the Mutual Information Dimension.
Proceedings of the IJCAI 2013, 2013

2012
Feature Selection via Dependence Maximization.
J. Mach. Learn. Res., 2012

A Kernel Two-Sample Test.
J. Mach. Learn. Res., 2012

easyGWAS: An integrated interspecies platform for performing genome-wide association studies
CoRR, 2012

ShapePheno: unsupervised extraction of shape phenotypes from biological image collections.
Bioinform., 2012

2011
Guest editorial to the special issue on inductive logic programming, mining and learning in graphs and statistical relational learning.
Mach. Learn., 2011

Weisfeiler-Lehman Graph Kernels.
J. Mach. Learn. Res., 2011

Efficient branch-and-bound techniques for two-locus association mapping.
BMC Bioinform., 2011

ccSVM: correcting Support Vector Machines for confounding factors in biological data classification.
Bioinform., 2011

Epistasis detection on quantitative phenotypes by exhaustive enumeration using GPUs.
Bioinform., 2011

Efficient inference in matrix-variate Gaussian models with \iid observation noise.
Proceedings of the Advances in Neural Information Processing Systems 24: 25th Annual Conference on Neural Information Processing Systems 2011. Proceedings of a meeting held 12-14 December 2011, 2011

Two-locus association mapping in subquadratic time.
Proceedings of the 17th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2011

Kernel Methods in Bioinformatics.
Proceedings of the Handbook of Statistical Bioinformatics., 2011

2010
Discriminative frequent subgraph mining with optimality guarantees.
Stat. Anal. Data Min., 2010

Spatio-Spectral Remote Sensing Image Classification With Graph Kernels.
IEEE Geosci. Remote. Sens. Lett., 2010

Graph Kernels.
J. Mach. Learn. Res., 2010

A Robust Bayesian Two-Sample Test for Detecting Intervals of Differential Gene Expression in Microarray Time Series.
J. Comput. Biol., 2010

Gene function prediction from synthetic lethality networks via ranking on demand.
Bioinform., 2010

Frequent subgraph discovery in dynamic networks.
Proceedings of the Eighth Workshop on Mining and Learning with Graphs, 2010

2009
Efficient graphlet kernels for large graph comparison.
Proceedings of the Twelfth International Conference on Artificial Intelligence and Statistics, 2009

A kernel method for unsupervised structured network inference.
Proceedings of the Twelfth International Conference on Artificial Intelligence and Statistics, 2009

Bayesian two-sample tests
CoRR, 2009

Near-optimal Supervised Feature Selection among Frequent Subgraphs.
Proceedings of the SIAM International Conference on Data Mining, 2009

A Robust Bayesian Two-Sample Test for Detecting Intervals of Differential Gene Expression in Microarray Time Series.
Proceedings of the Research in Computational Molecular Biology, 2009

Fast subtree kernels on graphs.
Proceedings of the Advances in Neural Information Processing Systems 22: 23rd Annual Conference on Neural Information Processing Systems 2009. Proceedings of a meeting held 7-10 December 2009, 2009

The graphlet spectrum.
Proceedings of the 26th Annual International Conference on Machine Learning, 2009

Discovering Temporal Patterns of Differential Gene Expression in Microarray Time Series.
Proceedings of the German Conference on Bioinformatics 2009, 2009

2008
The skew spectrum of graphs.
Proceedings of the Machine Learning, 2008

Metropolis Algorithms for Representative Subgraph Sampling.
Proceedings of the 8th IEEE International Conference on Data Mining (ICDM 2008), 2008

2007
Graph kernels.
PhD thesis, 2007

Future trends in data mining.
Data Min. Knowl. Discov., 2007

Graph Kernels For Disease Outcome Prediction From Protein-Protein Interaction Networks.
Proceedings of the Biocomputing 2007, 2007

Colored Maximum Variance Unfolding.
Proceedings of the Advances in Neural Information Processing Systems 20, 2007

An Efficient Sampling Scheme For Comparison of Large Graphs.
Proceedings of the Mining and Learning with Graphs, 2007

Gene selection via the BAHSIC family of algorithms.
Proceedings of the Proceedings 15th International Conference on Intelligent Systems for Molecular Biology (ISMB) & 6th European Conference on Computational Biology (ECCB), 2007

Supervised feature selection via dependence estimation.
Proceedings of the Machine Learning, 2007

A dependence maximization view of clustering.
Proceedings of the Machine Learning, 2007

Graph-Kerne [Graph Kernels].
Proceedings of the Ausgezeichnete Informatikdissertationen 2007, 2007

A Kernel Approach to Comparing Distributions.
Proceedings of the Twenty-Second AAAI Conference on Artificial Intelligence, 2007

2006
Kernel extrapolation.
Neurocomputing, 2006

VGM: visual graph mining.
Proceedings of the ACM SIGMOD International Conference on Management of Data, 2006

Class Prediction from Time Series Gene Expression Profiles Using Dynamical Systems Kernels.
Proceedings of the Biocomputing 2006, 2006

Fast Computation of Graph Kernels.
Proceedings of the Advances in Neural Information Processing Systems 19, 2006

Correcting Sample Selection Bias by Unlabeled Data.
Proceedings of the Advances in Neural Information Processing Systems 19, 2006

A Kernel Method for the Two-Sample-Problem.
Proceedings of the Advances in Neural Information Processing Systems 19, 2006

Integrating structured biological data by Kernel Maximum Mean Discrepancy.
Proceedings of the Proceedings 14th International Conference on Intelligent Systems for Molecular Biology 2006, 2006

Pattern Mining in Frequent Dynamic Subgraphs.
Proceedings of the 6th IEEE International Conference on Data Mining (ICDM 2006), 2006

3DString: a feature string kernel for 3D object classification on voxelized data.
Proceedings of the 2006 ACM CIKM International Conference on Information and Knowledge Management, 2006

2005
Protein function prediction via graph kernels.
Proceedings of the Proceedings Thirteenth International Conference on Intelligent Systems for Molecular Biology 2005, 2005

Shortest-Path Kernels on Graphs.
Proceedings of the 5th IEEE International Conference on Data Mining (ICDM 2005), 2005

Joint Regularization.
Proceedings of the 13th European Symposium on Artificial Neural Networks, 2005


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