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Djork-Arné Clevert
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2020 – today
- 2024
- [j10]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:
MELLODDY: Cross-pharma Federated Learning at Unprecedented Scale Unlocks Benefits in QSAR without Compromising Proprietary Information. J. Chem. Inf. Model. 64(7): 2331-2344 (2024) - [c9]Tuan Le, Julian Cremer, Frank Noé, Djork-Arné Clevert, Kristof T. Schütt:
Navigating the Design Space of Equivariant Diffusion-Based Generative Models for De Novo 3D Molecule Generation. ICLR 2024 - [i15]Julian Cremer, Tuan Le, Frank Noé, Djork-Arné Clevert, Kristof T. Schütt:
PILOT: Equivariant diffusion for pocket conditioned de novo ligand generation with multi-objective guidance via importance sampling. CoRR abs/2405.14925 (2024) - [i14]Mikhail Andronov, Natalia Andronova, Michael Wand, Jürgen Schmidhuber, Djork-Arné Clevert:
Accelerating the inference of string generation-based chemical reaction models for industrial applications. CoRR abs/2407.09685 (2024) - 2023
- [c8]Liang Xue
, Mykola Bordyuh
, Djork-Arné Clevert
, Robert Stanton
:
Benchmarking deep learning models and classical de novo sequencing tools for immunopeptidomics. BCB 2023: 61:1 - [i13]Marco Bertolini, Van-Khoa Le, Jake Pencharz, Andreas Poehlmann, Djork-Arné Clevert, Santiago Villalba, Floriane Montanari:
From slides (through tiles) to pixels: an explainability framework for weakly supervised models in pre-clinical pathology. CoRR abs/2302.01653 (2023) - [i12]Paula Torren-Peraire, Alan Kai Hassen, Samuel Genheden, Jonas Verhoeven, Djork-Arné Clevert, Mike Preuss, Igor V. Tetko:
Models Matter: The Impact of Single-Step Retrosynthesis on Synthesis Planning. CoRR abs/2308.05522 (2023) - [i11]Tuan Le, Julian Cremer, Frank Noé, Djork-Arné Clevert, Kristof Schütt:
Navigating the Design Space of Equivariant Diffusion-Based Generative Models for De Novo 3D Molecule Generation. CoRR abs/2309.17296 (2023) - 2022
- [c7]Tuan Le, Frank Noé, Djork-Arné Clevert:
Representation Learning on Biomolecular Structures Using Equivariant Graph Attention. LoG 2022: 30 - [c6]Robin Winter, Marco Bertolini, Tuan Le, Frank Noé, Djork-Arné Clevert:
Unsupervised Learning of Group Invariant and Equivariant Representations. NeurIPS 2022 - [i10]Robin Winter, Marco Bertolini, Tuan Le, Frank Noé, Djork-Arné Clevert:
Unsupervised Learning of Group Invariant and Equivariant Representations. CoRR abs/2202.07559 (2022) - [i9]Marco Bertolini, Djork-Arné Clevert, Floriane Montanari:
Explaining, Evaluating and Enhancing Neural Networks' Learned Representations. CoRR abs/2202.09374 (2022) - [i8]Tuan Le, Frank Noé, Djork-Arné Clevert:
Equivariant Graph Attention Networks for Molecular Property Prediction. CoRR abs/2202.09891 (2022) - 2021
- [j9]Paula A. Marin Zapata
, Sina Roth, Dirk Schmutzler, Thomas Wolf, Erica Manesso, Djork-Arné Clevert:
Self-supervised feature extraction from image time series in plant phenotyping using triplet networks. Bioinform. 37(6): 861-867 (2021) - [j8]Pedro B. P. S. Reis
, Djork-Arné Clevert, Miguel Machuqueiro
:
pKPDB: a protein data bank extension database of pKa and pI theoretical values. Bioinform. 38(1): 297-298 (2021) - [c5]Tuan Le
, Marco Bertolini
, Frank Noé
, Djork-Arné Clevert
:
Parameterized Hypercomplex Graph Neural Networks for Graph Classification. ICANN (3) 2021: 204-216 - [c4]Ryan Henderson, Djork-Arné Clevert, Floriane Montanari:
Improving Molecular Graph Neural Network Explainability with Orthonormalization and Induced Sparsity. ICML 2021: 4203-4213 - [c3]Robin Winter, Frank Noé, Djork-Arné Clevert:
Permutation-Invariant Variational Autoencoder for Graph-Level Representation Learning. NeurIPS 2021: 9559-9573 - [i7]Robin Winter, Frank Noé, Djork-Arné Clevert:
Auto-Encoding Molecular Conformations. CoRR abs/2101.01618 (2021) - [i6]Tuan Le, Marco Bertolini, Frank Noé, Djork-Arné Clevert:
Parameterized Hypercomplex Graph Neural Networks for Graph Classification. CoRR abs/2103.16584 (2021) - [i5]Robin Winter, Frank Noé, Djork-Arné Clevert:
Permutation-Invariant Variational Autoencoder for Graph-Level Representation Learning. CoRR abs/2104.09856 (2021) - [i4]Ryan Henderson, Djork-Arné Clevert, Floriane Montanari:
Improving Molecular Graph Neural Network Explainability with Orthonormalization and Induced Sparsity. CoRR abs/2105.04854 (2021) - 2020
- [j7]Robin Winter
, Joren Retel, Frank Noé, Djork-Arné Clevert, Andreas Steffen:
grünifai: interactive multiparameter optimization of molecules in a continuous vector space. Bioinform. 36(13): 4093-4094 (2020) - [i3]Ryan Henderson, Djork-Arné Clevert, Floriane Montanari:
Gini in a Bottleneck: Gotta Train Me the Right Way. CoRR abs/2010.04535 (2020)
2010 – 2019
- 2019
- [j6]Moritz Schaefer, Djork-Arné Clevert, Bertram Weiss, Andreas Steffen:
PAVOOC: designing CRISPR sgRNAs using 3D protein structures and functional domain annotations. Bioinform. 35(13): 2309-2310 (2019) - [j5]Markus Hofmarcher, Elisabeth Rumetshofer
, Djork-Arné Clevert, Sepp Hochreiter
, Günter Klambauer
:
Accurate Prediction of Biological Assays with High-Throughput Microscopy Images and Convolutional Networks. J. Chem. Inf. Model. 59(3): 1163-1171 (2019) - 2017
- [j4]Djork-Arné Clevert
, Thomas Unterthiner
, Gundula Povysil, Sepp Hochreiter
:
Rectified factor networks for biclustering of omics data. Bioinform. 33(14): i59-i66 (2017) - [i2]Robin Winter, Djork-Arné Clevert:
IVE-GAN: Invariant Encoding Generative Adversarial Networks. CoRR abs/1711.08646 (2017) - 2016
- [c2]Djork-Arné Clevert, Thomas Unterthiner, Sepp Hochreiter
:
Fast and Accurate Deep Network Learning by Exponential Linear Units (ELUs). ICLR (Poster) 2016 - 2015
- [c1]Djork-Arné Clevert, Andreas Mayr, Thomas Unterthiner, Sepp Hochreiter
:
Rectified Factor Networks. NIPS 2015: 1855-1863 - [i1]Djork-Arné Clevert, Thomas Unterthiner, Andreas Mayr, Hubert Ramsauer, Sepp Hochreiter
:
Rectified Factor Networks. CoRR abs/1502.06464 (2015) - 2010
- [j3]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
:
FABIA: factor analysis for bicluster acquisition. Bioinform. 26(12): 1520-1527 (2010)
2000 – 2009
- 2007
- [j2]Willem Talloen, Djork-Arné Clevert
, Sepp Hochreiter
, Dhammika Amaratunga, Luc Bijnens, Stefan Kass, Hinrich W. H. Göhlmann:
I/NI-calls for the exclusion of non-informative genes: a highly effective filtering tool for microarray data. Bioinform. 23(21): 2897-2902 (2007) - 2006
- [j1]Sepp Hochreiter
, Djork-Arné Clevert
, Klaus Obermayer:
A new summarization method for affymetrix probe level data. Bioinform. 22(8): 943-949 (2006)
Coauthor Index
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last updated on 2024-08-16 19:23 CEST by the dblp team
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