Denis Krompass

发表

A large-scale evaluation of computational protein function prediction

Daniel W. A. Buchan, Thomas A. Hopf, Mark N. Wass, 2013, Nature Methods.

Performance, Accuracy, and Web Server for Evolutionary Placement of Short Sequence Reads under Maximum Likelihood

Denis Krompass, A. Stamatakis, S. Berger, 2011, Systematic biology.

Ensemble Solutions for Link-Prediction in Knowledge Graphs

Volker Tresp, Denis Krompass, 2015 .

Towards a New Science of a Clinical Data Intelligence pdf

Volker Tresp, Denis Krompass, Volker Tresp, 2013, ArXiv.

Tensor-Train Recurrent Neural Networks for Video Classification

Volker Tresp, Yinchong Yang, Denis Krompass, 2017, ICML.

Large-scale factorization of type-constrained multi-relational data

Volker Tresp, Denis Krompass, Maximilian Nickel, 2014, 2014 International Conference on Data Science and Advanced Analytics (DSAA).

Non-Negative Tensor Factorization with RESCAL

Volker Tresp, Denis Krompass, Maximilian Nickel, 2013 .

FRAug: Tackling Federated Learning with Non-IID Features via Representation Augmentation

Denis Krompass, Volker Tresp, A. Frikha, 2022, ArXiv.

Proceedings of the 2014 International Conference on Data Science and Advanced Analytics (DSAA 2014)

Alexandre Termier, Shou-De Lin, Eric Gaussier, 2014 .

ARCADe: A Rapid Continual Anomaly Detector

Denis Krompass, Volker Tresp, A. Frikha, 2020, 2020 25th International Conference on Pattern Recognition (ICPR).

A Logistic Additive Approach for Relation Prediction in Multi-relational Data

Volker Tresp, Denis Krompass, Xueyan Jiang, 2013 .

A Logistic Additive Model for Relation Prediction in Multi-relational data.

Xueyan Jiang, Volker Tresp, Denis Krompass, 2013 .

Towards Data-Free Domain Generalization

T. Runkler, Denis Krompass, Volker Tresp, 2021, ArXiv.

FRAug: Tackling Federated Learning with Non-IID Features via Representation Augmentation

Denis Krompass, Volker Tresp, A. Frikha, 2022, ArXiv.

Towards Data-Free Domain Generalization

T. Runkler, Denis Krompass, Volker Tresp, 2021, ACML.

Discovery of New Multi-Level Features for Domain Generalization via Knowledge Corruption

Denis Krompass, Volker Tresp, A. Frikha, 2021, 2022 26th International Conference on Pattern Recognition (ICPR).

CL-CrossVQA: A Continual Learning Benchmark for Cross-Domain Visual Question Answering

Denis Krompass, Volker Tresp, A. Frikha, 2022, ArXiv.

Exploiting prior knowledge and latent variable representations for the statistical modeling and probabilistic querying of large knowledge graphs

Denis Krompass, Denis Krompass, 2015 .

Pruning Rogue Taxa Improves Phylogenetic Accuracy: An Efficient Algorithm and Webservice

Alexandros Stamatakis, Denis Krompass, Andre J. Aberer, 2012, Systematic biology.

Learning with Memory Embeddings pdf

Volker Tresp, Yinchong Yang, Denis Krompass, 2015, ArXiv.

Few-Shot One-Class Classification via Meta-Learning pdf

Volker Tresp, Ahmed Frikha, Denis Krompaß, 2019, AAAI.

Type-Constrained Representation Learning in Knowledge Graphs

Volker Tresp, Denis Krompass, Stephan Baier, 2015, SEMWEB.

Querying Factorized Probabilistic Triple Databases

Volker Tresp, Denis Krompass, Maximilian Nickel, 2014, SEMWEB.

Exploiting Latent Embeddings of Nominal Clinical Data for Predicting Hospital Readmission

Volker Tresp, Thomas Ganslandt, Martin Sedlmayr, 2015, KI - Künstliche Intelligenz.

Predicting the co-evolution of event and Knowledge Graphs

Volker Tresp, Yinchong Yang, Denis Krompass, 2015, 2016 19th International Conference on Information Fusion (FUSION).

Predicting Sequences of Clinical Events by Using a Personalized Temporal Latent Embedding Model

Volker Tresp, Danilo Schmidt, Denis Krompaß, 2015, 2015 International Conference on Healthcare Informatics.

FRAug: Tackling Federated Learning with Non-IID Features via Representation Augmentation

Denis Krompass, Volker Tresp, A. Frikha, 2022, 2023 IEEE/CVF International Conference on Computer Vision (ICCV).

Homology-based inference sets the bar high for protein function prediction

Thomas A. Hopf, B. Rost, Tobias Hamp, 2013, BMC Bioinformatics.

FedDAT: An Approach for Foundation Model Finetuning in Multi-Modal Heterogeneous Federated Learning

Denis Krompass, Volker Tresp, Jindong Gu, 2023, AAAI.