A new summarization method for affymetrix probe level data. - Sepp Hochreiter; Djork-Arné Clevert; Klaus Obermayer (Bioinform., 2006)

I/NI-calls for the exclusion of non-informative genes: a highly effective filtering tool for microarray data. - Willem Talloen; Djork-Arné Clevert; Sepp Hochreiter; Dhammika Amaratunga; Luc Bijnens; Stefan Kass; Hinrich W. H. Göhlmann (Bioinform., 2007)

FABIA: factor analysis for bicluster acquisition. - Sepp Hochreiter; Ulrich Bodenhofer; Martin Heusel; Andreas Mayr; Andreas Mitterecker; Adetayo Kasim; Tatsiana Khamiakova; Suzy Van Sanden; Dan Lin 004; Willem Talloen; Luc Bijnens; Hinrich W. H. Göhlmann; et al. (Bioinform., 2010)

Rectified Factor Networks. - Djork-Arné Clevert; Andreas Mayr; Thomas Unterthiner; Sepp Hochreiter (NIPS, 2015)

Rectified Factor Networks. - Djork-Arné Clevert; Thomas Unterthiner; Andreas Mayr; Hubert Ramsauer; Sepp Hochreiter (CoRR, 2015)

Fast and Accurate Deep Network Learning by Exponential Linear Units (ELUs). - Djork-Arné Clevert; Thomas Unterthiner; Sepp Hochreiter (ICLR (Poster), 2016)

Rectified factor networks for biclustering of omics data. - Djork-Arné Clevert; Thomas Unterthiner; Gundula Povysil; Sepp Hochreiter (Bioinform., 2017)

IVE-GAN: Invariant Encoding Generative Adversarial Networks. - Robin Winter; Djork-Arné Clevert (CoRR, 2017)

PAVOOC: designing CRISPR sgRNAs using 3D protein structures and functional domain annotations. - Moritz Schaefer; Djork-Arné Clevert; Bertram Weiss; Andreas Steffen (Bioinform., 2019)

Accurate Prediction of Biological Assays with High-Throughput Microscopy Images and Convolutional Networks. - Markus Hofmarcher; Elisabeth Rumetshofer; Djork-Arné Clevert; Sepp Hochreiter; Günter Klambauer (J. Chem. Inf. Model., 2019)

grünifai: interactive multiparameter optimization of molecules in a continuous vector space. - Robin Winter; Joren Retel; Frank Noé; Djork-Arné Clevert; Andreas Steffen (Bioinform., 2020)

Gini in a Bottleneck: Gotta Train Me the Right Way. - Ryan Henderson; Djork-Arné Clevert; Floriane Montanari (CoRR, 2020)

Parameterized Hypercomplex Graph Neural Networks for Graph Classification. - Tuan Le; Marco Bertolini; Frank Noé; Djork-Arné Clevert (ICANN (3), 2021)

Improving Molecular Graph Neural Network Explainability with Orthonormalization and Induced Sparsity. - Ryan Henderson; Djork-Arné Clevert; Floriane Montanari (ICML, 2021)

Permutation-Invariant Variational Autoencoder for Graph-Level Representation Learning. - Robin Winter; Frank Noé; Djork-Arné Clevert (NeurIPS, 2021)

pKPDB: a protein data bank extension database of pKa and pI theoretical values. - Pedro B. P. S. Reis; Djork-Arné Clevert; Miguel Machuqueiro (Bioinform., 2021)

Self-supervised feature extraction from image time series in plant phenotyping using triplet networks. - Paula A. Marin Zapata; Sina Roth; Dirk Schmutzler; Thomas Wolf; Erica Manesso; Djork-Arné Clevert (Bioinform., 2021)

Auto-Encoding Molecular Conformations. - Robin Winter; Frank Noé; Djork-Arné Clevert (CoRR, 2021)

Representation Learning on Biomolecular Structures Using Equivariant Graph Attention. - Tuan Le; Frank Noé; Djork-Arné Clevert (LoG, 2022)

Unsupervised Learning of Group Invariant and Equivariant Representations. - Robin Winter; Marco Bertolini; Tuan Le; Frank Noé; Djork-Arné Clevert (NeurIPS, 2022)

Equivariant Graph Attention Networks for Molecular Property Prediction. - Tuan Le; Frank Noé; Djork-Arné Clevert (CoRR, 2022)

Benchmarking deep learning models and classical de novo sequencing tools for immunopeptidomics. - Liang Xue; Mykola Bordyuh; Djork-Arné Clevert; Robert Stanton (BCB, 2023)

Explaining, Evaluating and Enhancing Neural Networks' Learned Representations. - Marco Bertolini; Djork-Arné Clevert; Floriane Montanari (ICANN (5), 2023)

From slides (through tiles) to pixels: an explainability framework for weakly supervised models in pre-clinical pathology. - Marco Bertolini; Van-Khoa Le; Jake Pencharz; Andreas Poehlmann; Djork-Arné Clevert; Santiago Villalba; Floriane Montanari (CoRR, 2023)

Models Matter: The Impact of Single-Step Retrosynthesis on Synthesis Planning. - Paula Torren-Peraire; Alan Kai Hassen; Samuel Genheden; Jonas Verhoeven; Djork-Arné Clevert; Mike Preuss; Igor V. Tetko (CoRR, 2023)

Curating Reagents in Chemical Reaction Data with an Interactive Reagent Space Map. - Mikhail Andronov; Natalia Andronova; Michael Wand 002; Jürgen Schmidhuber; Djork-Arné Clevert (AIDD@ICANN, 2024)

Enhancing Interpretability in Molecular Property Prediction with Contextual Explanations of Molecular Graphical Depictions. - Marco Bertolini; Linlin Zhao; Floriane Montanari; Djork-Arné Clevert (AIDD@ICANN, 2024)

Latent-Conditioned Equivariant Diffusion for Structure-Based De Novo Ligand Generation. - Julian Cremer; Tuan Le; Djork-Arné Clevert; Kristof T. Schütt (AIDD@ICANN, 2024)

Navigating the Design Space of Equivariant Diffusion-Based Generative Models for De Novo 3D Molecule Generation. - Tuan Le; Julian Cremer; Frank Noé; Djork-Arné Clevert; Kristof T. Schütt (ICLR, 2024)

PILOT: Equivariant diffusion for pocket conditioned de novo ligand generation with multi-objective guidance via importance sampling. - Julian Cremer; Tuan Le; Frank Noé; Djork-Arné Clevert; Kristof T. Schütt (CoRR, 2024)

Knowledge Graph Based Agent for Complex, Knowledge-Intensive QA in Medicine. - Xiaorui Su 001; Yibo Wang 001; Shanghua Gao; Xiaolong Liu; Valentina Giunchiglia; Djork-Arné Clevert; Marinka Zitnik (CoRR, 2024)

MELLODDY: Cross-pharma Federated Learning at Unprecedented Scale Unlocks Benefits in QSAR without Compromising Proprietary Information. - Wouter Heyndrickx; Lewis H. Mervin; Tobias Morawietz; Noé Sturm; Lukas Friedrich; Adam Zalewski; Anastasia Pentina; Lina Humbeck; Martijn Oldenhof; Ritsuya Niwayama; Peter Schmidtke; Nikolas Fechner; et al. (J. Chem. Inf. Model., 2024)

A call for an industry-led initiative to critically assess machine learning for real-world drug discovery. - Cas Wognum; Jeremy R. Ash; Matteo Aldeghi; Raquel Rodríguez-Pérez; Cheng Fang; Alan C. Cheng; Daniel J. Price; Djork-Arné Clevert; Ola Engkvist; W. Patrick Walters (Nat. Mac. Intell., 2024)

KGARevion: An AI Agent for Knowledge-Intensive Biomedical QA. - Xiaorui Su 001; Yibo Wang 001; Shanghua Gao; Xiaolong Liu; Valentina Giunchiglia; Djork-Arné Clevert; Marinka Zitnik (ICLR, 2025)

Generative Modeling on Lie Groups via Euclidean Generalized Score Matching. - Marco Bertolini; Tuan Le; Djork-Arné Clevert (CoRR, 2025)

FLOWR: Flow Matching for Structure-Aware De Novo, Interaction- and Fragment-Based Ligand Generation. - Julian Cremer; Ross Irwin; Alessandro Tibo; Jon Paul Janet; Simon Olsson; Djork-Arné Clevert (CoRR, 2025)

Fast and scalable retrosynthetic planning with a transformer neural network and speculative beam search. - Mikhail Andronov; Natalia Andronova; Michael Wand 002; Jürgen Schmidhuber; Djork-Arné Clevert (CoRR, 2025)

Accelerating the inference of string generation-based chemical reaction models for industrial applications. - Mikhail Andronov; Natalia Andronova; Michael Wand 002; Jürgen Schmidhuber; Djork-Arné Clevert (J. Cheminformatics, 2025)

Generate what you can make: achieving in-house synthesizability with readily available resources in de novo drug design. - Alan Kai Hassen; Martin Sícho; Yorick J. van Aalst; Mirjam C. W. Huizenga; Darcy N. R. Reynolds; Sohvi Luukkonen; Andrius Bernatavicius; Djork-Arné Clevert; Antonius P. A. Janssen; Gerard J. P. van Westen; Mike Preuss (J. Cheminformatics, 2025)

Equivariant diffusion for structure-based de novo ligand generation with latent-conditioning. - Tuan Le; Julian Cremer; Djork-Arné Clevert; Kristof T. Schütt (J. Cheminformatics, 2025)

Advanced machine learning for innovative drug discovery. - Igor V. Tetko; Djork-Arné Clevert (J. Cheminformatics, 2025)