Djork-Arné Clevert | DeepAI

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Featured Co-authors

Sepp Hochreiter
47 publications
Frank Noé
39 publications
Mike Preuss
30 publications
Andreas Mayr
22 publications
Thomas Unterthiner
20 publications
Robin Winter
4 publications
Tuan Le
4 publications
Ryan Henderson
3 publications
Floriane Montanari
3 publications
Marco Bertolini
3 publications
Van-Khoa Le
2 publications

∙ 08/10/2023

Models Matter: The Impact of Single-Step Retrosynthesis on Synthesis Planning

Retrosynthesis consists of breaking down a chemical compound recursively...

0 Paula Torren-Peraire, et al. ∙

∙ 02/03/2023

From slides (through tiles) to pixels: an explainability framework for weakly supervised models in pre-clinical pathology

In pre-clinical pathology, there is a paradox between the abundance of r...

0 Marco Bertolini, et al. ∙

∙ 02/20/2022

Equivariant Graph Attention Networks for Molecular Property Prediction

Learning and reasoning about 3D molecular structures with varying size i...

6 Tuan Le, et al. ∙

∙ 02/15/2022

Unsupervised Learning of Group Invariant and Equivariant Representations

Equivariant neural networks, whose hidden features transform according t...

9 Robin Winter, et al. ∙

∙ 05/11/2021

Improving Molecular Graph Neural Network Explainability with Orthonormalization and Induced Sparsity

Rationalizing which parts of a molecule drive the predictions of a molec...

0 Ryan Henderson, et al. ∙

∙ 04/20/2021

Permutation-Invariant Variational Autoencoder for Graph-Level Representation Learning

Recently, there has been great success in applying deep neural networks ...

0 Robin Winter, et al. ∙

∙ 03/30/2021

Parameterized Hypercomplex Graph Neural Networks for Graph Classification

Despite recent advances in representation learning in hypercomplex (HC) ...

0 Tuan Le, et al. ∙

∙ 01/05/2021

Auto-Encoding Molecular Conformations

In this work we introduce an Autoencoder for molecular conformations. Ou...

0 Robin Winter, et al. ∙

∙ 10/09/2020

Gini in a Bottleneck: Gotta Train Me the Right Way

Due to the nature of deep learning approaches, it is inherently difficul...

0 Ryan Henderson, et al. ∙

∙ 11/23/2017

IVE-GAN: Invariant Encoding Generative Adversarial Networks

Generative adversarial networks (GANs) are a powerful framework for gene...

0 Robin Winter, et al. ∙

∙ 11/23/2015

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

We introduce the "exponential linear unit" (ELU) which speeds up learnin...

0 Djork-Arné Clevert, et al. ∙

∙ 02/23/2015

Rectified Factor Networks

We propose rectified factor networks (RFNs) to efficiently construct ver...

0 Djork-Arné Clevert, et al. ∙

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