Detection of viral sequence fragments of HIV-1 subfamilies yet unknown. - Thomas Unterthiner; Anne-Kathrin Schultz; Jan Bulla; Burkhard Morgenstern; Mario Stanke; Ingo Bulla (BMC Bioinform., 2011)

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

Rchemcpp: a web service for structural analoging in ChEMBL, Drugbank and the Connectivity Map. - Günter Klambauer; Martin Wischenbart; Michael Mahr; Thomas Unterthiner; Andreas Mayr; Sepp Hochreiter (Bioinform., 2015)

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

Toxicity Prediction using Deep Learning. - Thomas Unterthiner; Andreas Mayr; Günter Klambauer; 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)

GANs Trained by a Two Time-Scale Update Rule Converge to a Local Nash Equilibrium. - Martin Heusel; Hubert Ramsauer; Thomas Unterthiner; Bernhard Nessler; Sepp Hochreiter (NIPS, 2017)

Self-Normalizing Neural Networks. - Günter Klambauer; Thomas Unterthiner; Andreas Mayr; Sepp Hochreiter (NIPS, 2017)

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

GANs Trained by a Two Time-Scale Update Rule Converge to a Nash Equilibrium. - Martin Heusel; Hubert Ramsauer; Thomas Unterthiner; Bernhard Nessler; Günter Klambauer; Sepp Hochreiter (CoRR, 2017)

Coulomb GANs: Provably Optimal Nash Equilibria via Potential Fields. - Thomas Unterthiner; Bernhard Nessler; Günter Klambauer; Martin Heusel; Hubert Ramsauer; Sepp Hochreiter (CoRR, 2017)

Coulomb GANs: Provably Optimal Nash Equilibria via Potential Fields. - Thomas Unterthiner; Bernhard Nessler; Calvin Seward; Günter Klambauer; Martin Heusel; Hubert Ramsauer; Sepp Hochreiter (ICLR (Poster), 2018)

First Order Generative Adversarial Networks. - Calvin Seward; Thomas Unterthiner; Urs Bergmann; Nikolay Jetchev; Sepp Hochreiter (ICML, 2018)

Fréchet ChemblNet Distance: A metric for generative models for molecules. - Kristina Preuer; Philipp Renz; Thomas Unterthiner; Sepp Hochreiter; Günter Klambauer (CoRR, 2018)

RUDDER: Return Decomposition for Delayed Rewards. - Jose A. Arjona-Medina; Michael Gillhofer; Michael Widrich; Thomas Unterthiner; Sepp Hochreiter (CoRR, 2018)

Towards Accurate Generative Models of Video: A New Metric & Challenges. - Thomas Unterthiner; Sjoerd van Steenkiste; Karol Kurach; Raphaël Marinier; Marcin Michalski; Sylvain Gelly (CoRR, 2018)

Fréchet ChemNet Distance: A Metric for Generative Models for Molecules in Drug Discovery. - Kristina Preuer; Philipp Renz; Thomas Unterthiner; Sepp Hochreiter; Günter Klambauer (J. Chem. Inf. Model., 2018)

FVD: A new Metric for Video Generation. - Thomas Unterthiner; Sjoerd van Steenkiste; Karol Kurach; Raphaël Marinier; Marcin Michalski; Sylvain Gelly (DGS@ICLR, 2019)

RUDDER: Return Decomposition for Delayed Rewards. - Jose A. Arjona-Medina; Michael Gillhofer; Michael Widrich; Thomas Unterthiner; Johannes Brandstetter; Sepp Hochreiter (NeurIPS, 2019)

Interpretable Deep Learning in Drug Discovery. - Kristina Preuer; Günter Klambauer; Friedrich Rippmann; Sepp Hochreiter; Thomas Unterthiner (CoRR, 2019)

Visual Scene Understanding for Autonomous Driving Using Semantic Segmentation. - Markus Hofmarcher; Thomas Unterthiner; Jose A. Arjona-Medina; Günter Klambauer; Sepp Hochreiter; Bernhard Nessler (Explainable AI, 2019)

Interpretable Deep Learning in Drug Discovery. - Kristina Preuer; Günter Klambauer; Friedrich Rippmann; Sepp Hochreiter; Thomas Unterthiner (Explainable AI, 2019)

Object-Centric Learning with Slot Attention. - Francesco Locatello; Dirk Weissenborn; Thomas Unterthiner; Aravindh Mahendran; Georg Heigold; Jakob Uszkoreit; Alexey Dosovitskiy; Thomas Kipf (NeurIPS, 2020)

Predicting Neural Network Accuracy from Weights. - Thomas Unterthiner; Daniel Keysers; Sylvain Gelly; Olivier Bousquet; Ilya O. Tolstikhin (CoRR, 2020)

Differentiable Patch Selection for Image Recognition. - Jean-Baptiste Cordonnier; Aravindh Mahendran; Alexey Dosovitskiy; Dirk Weissenborn; Jakob Uszkoreit; Thomas Unterthiner (CVPR, 2021)

Understanding Robustness of Transformers for Image Classification. - Srinadh Bhojanapalli; Ayan Chakrabarti; Daniel Glasner; Daliang Li; Thomas Unterthiner; Andreas Veit (ICCV, 2021)

An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale. - Alexey Dosovitskiy; Lucas Beyer; Alexander Kolesnikov 003; Dirk Weissenborn; Xiaohua Zhai; Thomas Unterthiner; Mostafa Dehghani 001; Matthias Minderer; Georg Heigold; Sylvain Gelly; Jakob Uszkoreit; Neil Houlsby (ICLR, 2021)

Do Vision Transformers See Like Convolutional Neural Networks? - Maithra Raghu; Thomas Unterthiner; Simon Kornblith; Chiyuan Zhang; Alexey Dosovitskiy (NeurIPS, 2021)

MLP-Mixer: An all-MLP Architecture for Vision. - Ilya O. Tolstikhin; Neil Houlsby; Alexander Kolesnikov 003; Lucas Beyer; Xiaohua Zhai; Thomas Unterthiner; Jessica Yung; Andreas Steiner 001; Daniel Keysers; Jakob Uszkoreit; Mario Lucic; Alexey Dosovitskiy (NeurIPS, 2021)

GradMax: Growing Neural Networks using Gradient Information. - Utku Evci; Bart van Merrienboer; Thomas Unterthiner; Fabian Pedregosa; Max Vladymyrov (ICLR, 2022)

Accurate Machine Learned Quantum-Mechanical Force Fields for Biomolecular Simulations. - Oliver T. Unke; Martin Stöhr; Stefan Ganscha; Thomas Unterthiner; Hartmut Maennel; Sergii Kashubin; Daniel Ahlin; Michael Gastegger; Leonardo Medrano Sandonas; Alexandre Tkatchenko; Klaus-Robert Müller (CoRR, 2022)

Getting aligned on representational alignment. - Ilia Sucholutsky; Lukas Muttenthaler; Adrian Weller; Andi Peng; Andreea Bobu; Been Kim; Bradley C. Love; Erin Grant; Jascha Achterberg; Joshua B. Tenenbaum; Katherine M. Collins; Katherine L. Hermann; et al. (CoRR, 2023)

Set Learning for Accurate and Calibrated Models. - Lukas Muttenthaler; Robert A. Vandermeulen; Qiuyi Zhang 001; Thomas Unterthiner; Klaus-Robert Müller (ICLR, 2024)

PaliGemma: A versatile 3B VLM for transfer. - Lucas Beyer; Andreas Steiner 001; André Susano Pinto; Alexander Kolesnikov 003; Xiao Wang 038; Daniel Salz; Maxim Neumann; Ibrahim Alabdulmohsin; Michael Tschannen; Emanuele Bugliarello; Thomas Unterthiner; Daniel Keysers; et al. (CoRR, 2024)

Aligning Machine and Human Visual Representations across Abstraction Levels. - Lukas Muttenthaler; Klaus Greff; Frieda Born; Bernhard Spitzer; Simon Kornblith; Michael C. Mozer; Klaus-Robert Müller; Thomas Unterthiner; Andrew K. Lampinen (CoRR, 2024)