Djork-Arné Clevert

According to our database, Djork-Arné Clevert authored at least 34 papers between 2006 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

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

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, Jaak Simm, Adam Arany, Nicolas Drizard, Rama Jabal, Arina Afanasyeva, Regis Loeb, Shlok Verma, Simon Harnqvist, Matthew Holmes, Balazs Pejo, Maria Telenczuk, Nicholas Holway, Arne Dieckmann, Nicola Rieke, Friederike Zumsande, Djork-Arné Clevert, Michael Krug, Christopher N. Luscombe, Darren V. S. Green, Peter Ertl, Peter Antal, David Marcus, Nicolas Do Huu, Hideyoshi Fuji, Stephen D. Pickett, Gergely Ács, Eric Boniface, Bernd Beck, Yax Sun, Arnaud Gohier, Friedrich Rippmann, Ola Engkvist, Andreas H. Göller, Yves Moreau, Mathieu N. Galtier, Ansgar Schuffenhauer, Hugo Ceulemans

J. Chem. Inf. Model., 2024

Knowledge Graph Based Agent for Complex, Knowledge-Intensive QA in Medicine.

Xiaorui Su, Yibo Wang, Shanghua Gao, Xiaolong Liu, Valentina Giunchiglia, Djork-Arné Clevert, Marinka Zitnik

CoRR, 2024

Accelerating the inference of string generation-based chemical reaction models for industrial applications.

Mikhail Andronov, Natalia Andronova, Michael Wand, Jürgen Schmidhuber, Djork-Arné Clevert

CoRR, 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

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

Proceedings of the Twelfth International Conference on Learning Representations, 2024

Latent-Conditioned Equivariant Diffusion for Structure-Based De Novo Ligand Generation.

Julian Cremer, Tuan Le, Djork-Arné Clevert, Kristof T. Schütt

Proceedings of the AI in Drug Discovery - First International Workshop, 2024

Enhancing Interpretability in Molecular Property Prediction with Contextual Explanations of Molecular Graphical Depictions.

Marco Bertolini, Linlin Zhao, Floriane Montanari, Djork-Arné Clevert

Proceedings of the AI in Drug Discovery - First International Workshop, 2024

Curating Reagents in Chemical Reaction Data with an Interactive Reagent Space Map.

Mikhail Andronov, Natalia Andronova, Michael Wand, Jürgen Schmidhuber, Djork-Arné Clevert

Proceedings of the AI in Drug Discovery - First International Workshop, 2024

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

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

Explaining, Evaluating and Enhancing Neural Networks' Learned Representations.

Marco Bertolini, Djork-Arné Clevert, Floriane Montanari

Proceedings of the Artificial Neural Networks and Machine Learning, 2023

Benchmarking deep learning models and classical de novo sequencing tools for immunopeptidomics.

Liang Xue, Mykola Bordyuh, Djork-Arné Clevert, Robert Stanton

Proceedings of the 14th ACM International Conference on Bioinformatics, 2023

2022

Equivariant Graph Attention Networks for Molecular Property Prediction.

Tuan Le, Frank Noé, Djork-Arné Clevert

CoRR, 2022

Unsupervised Learning of Group Invariant and Equivariant Representations.

Robin Winter, Marco Bertolini, Tuan Le, Frank Noé, Djork-Arné Clevert

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Representation Learning on Biomolecular Structures Using Equivariant Graph Attention.

Tuan Le, Frank Noé, Djork-Arné Clevert

Proceedings of the Learning on Graphs Conference, 2022

2021

Auto-Encoding Molecular Conformations.

Robin Winter, Frank Noé, Djork-Arné Clevert

CoRR, 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

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

Permutation-Invariant Variational Autoencoder for Graph-Level Representation Learning.

Robin Winter, Frank Noé, Djork-Arné Clevert

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Improving Molecular Graph Neural Network Explainability with Orthonormalization and Induced Sparsity.

Ryan Henderson, Djork-Arné Clevert, Floriane Montanari

Proceedings of the 38th International Conference on Machine Learning, 2021

Parameterized Hypercomplex Graph Neural Networks for Graph Classification.

Tuan Le, Marco Bertolini, Frank Noé, Djork-Arné Clevert

Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2021, 2021

2020

Gini in a Bottleneck: Gotta Train Me the Right Way.

Ryan Henderson, Djork-Arné Clevert, Floriane Montanari

CoRR, 2020

grünifai: interactive multiparameter optimization of molecules in a continuous vector space.

Robin Winter, Joren Retel, Frank Noé, Djork-Arné Clevert, Andreas Steffen

Bioinform., 2020

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

PAVOOC: designing CRISPR sgRNAs using 3D protein structures and functional domain annotations.

Moritz Schaefer, Djork-Arné Clevert, Bertram Weiss, Andreas Steffen

Bioinform., 2019

2017

IVE-GAN: Invariant Encoding Generative Adversarial Networks.

Robin Winter, Djork-Arné Clevert

CoRR, 2017

Rectified factor networks for biclustering of omics data.

Djork-Arné Clevert, Thomas Unterthiner, Gundula Povysil, Sepp Hochreiter

Bioinform., 2017

2016

Fast and Accurate Deep Network Learning by Exponential Linear Units (ELUs).

Djork-Arné Clevert, Thomas Unterthiner, Sepp Hochreiter

Proceedings of the 4th International Conference on Learning Representations, 2016

2015

Rectified Factor Networks.

Djork-Arné Clevert, Thomas Unterthiner, Andreas Mayr, Hubert Ramsauer, Sepp Hochreiter

CoRR, 2015

Rectified Factor Networks.

Djork-Arné Clevert, Andreas Mayr, Thomas Unterthiner, Sepp Hochreiter

Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

2010

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, Willem Talloen, Luc Bijnens, Hinrich W. H. Göhlmann, Ziv Shkedy, Djork-Arné Clevert

Bioinform., 2010

2007

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

2006

A new summarization method for affymetrix probe level data.

Sepp Hochreiter, Djork-Arné Clevert, Klaus Obermayer

Bioinform., 2006