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20142026
most citedGANs Trained by a Two Time-Scale Update Rule Converge to a Local Nash Equilibrium

4.5k citations · 8.5k across the 90 of their papers we have counts for

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Showing 2021Show all

7 papers · 1 filter

cs.LG2021★ 2 cited

A Dataset Perspective on Offline Reinforcement Learning

Kajetan Schweighofer, Andreas Radler, Marius-Constantin Dinu +5

The application of Reinforcement Learning (RL) in real world environments can be expensive or risky due to sub-optimal policies during training. In Offline RL, this problem is avoi…

cs.LG2021★ 30 cited

CLOOB: Modern Hopfield Networks with InfoLOOB Outperform CLIP

Andreas Fürst, Elisabeth Rumetshofer, Johannes Lehner +8

CLIP yielded impressive results on zero-shot transfer learning tasks and is considered as a foundation model like BERT or GPT3. CLIP vision models that have a rich representation a…

cs.LG2021★ 3 cited

Boundary Graph Neural Networks for 3D Simulations

Andreas Mayr, Sebastian Lehner, Arno Mayrhofer +3

The abundance of data has given machine learning considerable momentum in natural sciences and engineering, though modeling of physical processes is often difficult. A particularly…

cs.LG2021★ 1 cited

Learning 3D Granular Flow Simulations

Andreas Mayr, Sebastian Lehner, Arno Mayrhofer +3

Recently, the application of machine learning models has gained momentum in natural sciences and engineering, which is a natural fit due to the abundance of data in these fields. H…

cs.LG2021★ 3 cited

Modern Hopfield Networks for Few- and Zero-Shot Reaction Template Prediction

Philipp Seidl, Philipp Renz, Natalia Dyubankova +6

Finding synthesis routes for molecules of interest is an essential step in the discovery of new drugs and materials. To find such routes, computer-assisted synthesis planning (CASP…

stat.ML2021★ 7 cited

Trusted Artificial Intelligence: Towards Certification of Machine Learning Applications

Philip Matthias Winter, Sebastian Eder, Johannes Weissenböck +5

Artificial Intelligence is one of the fastest growing technologies of the 21st century and accompanies us in our daily lives when interacting with technical applications. However,…

cs.LG2021★ 3 cited

MC-LSTM: Mass-Conserving LSTM

Pieter-Jan Hoedt, Frederik Kratzert, Daniel Klotz +5

The success of Convolutional Neural Networks (CNNs) in computer vision is mainly driven by their strong inductive bias, which is strong enough to allow CNNs to solve vision-related…