output
20062021
most citedObservation of a new particle in the search for the Standard Model Higgs boson with the ATLAS detector at the LHC

10.9k citations

Showing 2021Show all

16 papers · 1 filter

cs.LG20218 cited

Hierarchical Reinforcement Learning with Timed Subgoals

Nico Gürtler, Dieter Büchler, Georg Martius

Hierarchical reinforcement learning (HRL) holds great potential for sample-efficient learning on challenging long-horizon tasks. In particular, letting a higher level assign subgoa…

cs.CV2021

On the Frequency Bias of Generative Models

Katja Schwarz, Yiyi Liao, Andreas Geiger

The key objective of Generative Adversarial Networks (GANs) is to generate new data with the same statistics as the provided training data. However, multiple recent works show that…

cs.CV2021

Projected GANs Converge Faster

Axel Sauer, Kashyap Chitta, Jens Müller +1

Generative Adversarial Networks (GANs) produce high-quality images but are challenging to train. They need careful regularization, vast amounts of compute, and expensive hyper-para…

cs.CV20212 cited

Neural Relightable Participating Media Rendering

Quan Zheng, Gurprit Singh, Hans-Peter Seidel

Learning neural radiance fields of a scene has recently allowed realistic novel view synthesis of the scene, but they are limited to synthesize images under the original fixed ligh…

cs.CV2021

Learning Realistic Human Reposing using Cyclic Self-Supervision with 3D Shape, Pose, and Appearance Consistency

Soubhik Sanyal, Alex Vorobiov, Timo Bolkart +5

Synthesizing images of a person in novel poses from a single image is a highly ambiguous task. Most existing approaches require paired training images; i.e. images of the same pers…

cs.CL2021

PASTE: A Tagging-Free Decoding Framework Using Pointer Networks for Aspect Sentiment Triplet Extraction

Rajdeep Mukherjee, Tapas Nayak, Yash Butala +2

Aspect Sentiment Triplet Extraction (ASTE) deals with extracting opinion triplets, consisting of an opinion target or aspect, its associated sentiment, and the corresponding opinio…