Thomas Unterthiner

Orcid: 0000-0001-5361-3087

According to our database¹, Thomas Unterthiner authored at least 33 papers between 2011 and 2023.

Collaborative distances:

Dijkstra number² of four.
Erdős number³ of three.

Timeline

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In proceedings

Article

PhD thesis

Dataset

Other

Bibliography

2023

Getting aligned on representational alignment.

[BibT_eX]

[DOI]

CoRR, 2023

Set Learning for Accurate and Calibrated Models.

[BibT_eX]

[DOI]

Lukas Muttenthaler

Robert A. Vandermeulen

Qiuyi Zhang

Thomas Unterthiner

Klaus-Robert Müller

CoRR, 2023

2022

Accurate Machine Learned Quantum-Mechanical Force Fields for Biomolecular Simulations.

[BibT_eX]

[DOI]

Leonardo Medrano Sandonas

Alexandre Tkatchenko

Klaus-Robert Müller

CoRR, 2022

GradMax: Growing Neural Networks using Gradient Information.

[BibT_eX]

[DOI]

Proceedings of the Tenth International Conference on Learning Representations, 2022

2021

MLP-Mixer: An all-MLP Architecture for Vision.

[BibT_eX]

[DOI]

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

Do Vision Transformers See Like Convolutional Neural Networks?

[BibT_eX]

[DOI]

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

An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale.

[BibT_eX]

[DOI]

Proceedings of the 9th International Conference on Learning Representations, 2021

Understanding Robustness of Transformers for Image Classification.

[BibT_eX]

[DOI]

Proceedings of the 2021 IEEE/CVF International Conference on Computer Vision, 2021

Differentiable Patch Selection for Image Recognition.

[BibT_eX]

[DOI]

Jean-Baptiste Cordonnier

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021

2020

Predicting Neural Network Accuracy from Weights.

[BibT_eX]

[DOI]

CoRR, 2020

Object-Centric Learning with Slot Attention.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

2019

Interpretable Deep Learning in Drug Discovery.

[BibT_eX]

[DOI]

Proceedings of the Explainable AI: Interpreting, 2019

Visual Scene Understanding for Autonomous Driving Using Semantic Segmentation.

[BibT_eX]

[DOI]

Markus Hofmarcher

Thomas Unterthiner

Jose A. Arjona-Medina

Günter Klambauer

Sepp Hochreiter

Bernhard Nessler

Proceedings of the Explainable AI: Interpreting, 2019

Interpretable Deep Learning in Drug Discovery.

[BibT_eX]

[DOI]

CoRR, 2019

RUDDER: Return Decomposition for Delayed Rewards.

[BibT_eX]

[DOI]

Jose A. Arjona-Medina

Michael Gillhofer

Michael Widrich

Thomas Unterthiner

Johannes Brandstetter

Sepp Hochreiter

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

FVD: A new Metric for Video Generation.

[BibT_eX]

[DOI]

Thomas Unterthiner

Sjoerd van Steenkiste

Proceedings of the Deep Generative Models for Highly Structured Data, 2019

2018

Fréchet ChemNet Distance: A Metric for Generative Models for Molecules in Drug Discovery.

[BibT_eX]

[DOI]

J. Chem. Inf. Model., 2018

Towards Accurate Generative Models of Video: A New Metric & Challenges.

[BibT_eX]

[DOI]

Thomas Unterthiner

Sjoerd van Steenkiste

CoRR, 2018

RUDDER: Return Decomposition for Delayed Rewards.

[BibT_eX]

[DOI]

Jose A. Arjona-Medina

CoRR, 2018

Fréchet ChemblNet Distance: A metric for generative models for molecules.

[BibT_eX]

[DOI]

CoRR, 2018

First Order Generative Adversarial Networks.

[BibT_eX]

[DOI]

Proceedings of the 35th International Conference on Machine Learning, 2018

Coulomb GANs: Provably Optimal Nash Equilibria via Potential Fields.

[BibT_eX]

[DOI]

Proceedings of the 6th International Conference on Learning Representations, 2018

2017

Coulomb GANs: Provably Optimal Nash Equilibria via Potential Fields.

[BibT_eX]

[DOI]

CoRR, 2017

GANs Trained by a Two Time-Scale Update Rule Converge to a Nash Equilibrium.

[BibT_eX]

[DOI]

CoRR, 2017

Rectified factor networks for biclustering of omics data.

[BibT_eX]

[DOI]

Bioinform., 2017

Self-Normalizing Neural Networks.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

GANs Trained by a Two Time-Scale Update Rule Converge to a Local Nash Equilibrium.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

2016

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

[BibT_eX]

[DOI]

Djork-Arné Clevert

Thomas Unterthiner

Sepp Hochreiter

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

2015

Toxicity Prediction using Deep Learning.

[BibT_eX]

[DOI]

CoRR, 2015

Rectified Factor Networks.

[BibT_eX]

[DOI]

CoRR, 2015

Rchemcpp: a web service for structural analoging in ChEMBL, Drugbank and the Connectivity Map.

[BibT_eX]

[DOI]

Bioinform., 2015

Rectified Factor Networks.

[BibT_eX]

[DOI]

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

2011

Detection of viral sequence fragments of HIV-1 subfamilies yet unknown.

[BibT_eX]

[DOI]

BMC Bioinform., 2011

Thomas Unterthiner

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