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Semi-supervised Gated Recurrent Neural Networks for Robotic Terrain Classification
AhmadrezaAhmadi, TønnesNygaard, NavindaKottege....
Published date-11/24/2020
LeggedRobots
Legged robots are popular candidates for missions in challenging terrains due to the wide variety of locomotion strategies they can employ. Terrain classification is a key enabling technology for autonomous …
Adversarial Generation of Continuous Images
IvanSkorokhodov, SavvaIgnatyev, MohamedElhoseiny....
Published date-11/24/2020
ImageGeneration
In most existing learning systems, images are typically viewed as 2D pixel arrays. However, in another paradigm gaining popularity, a 2D image is represented as an implicit neural representation (INR) …
Lipophilicity Prediction with Multitask Learning and Molecular Substructures Representation
NinaLukashina, AlisaAlenicheva, ElizavetaVlasova....
Published date-11/24/2020
Lipophilicity is one of the factors determining the permeability of the cell membrane to a drug molecule. Hence, accurate lipophilicity prediction is an essential step in the development of new …
Play Fair: Frame Attributions in Video Models
WillPrice, DimaDamen....
Published date-11/24/2020
ActionRecognition, RelationalReasoning
In this paper, we introduce an attribution method for explaining action recognition models. Such models fuse information from multiple frames within a video, through score aggregation or relational reasoning. We …
DeepShadows: Separating Low Surface Brightness Galaxies from Artifacts using Deep Learning
DimitriosTanoglidis, AleksandraĆiprijanović, AlexDrlica-Wagner....
Published date-11/24/2020
TransferLearning
Searches for low-surface-brightness galaxies (LSBGs) in galaxy surveys are plagued by the presence of a large number of artifacts (e.g., objects blended in the diffuse light from stars and galaxies, …
Language Generation via Combinatorial Constraint Satisfaction: A Tree Search Enhanced Monte-Carlo Approach
MaosenZhang, NanJiang, LeiLI....
Published date-11/24/2020
LanguageModelling, TextGeneration
Generating natural language under complex constraints is a principled formulation towards controllable text generation. We present a framework to allow specification of combinatorial constraints for sentence generation. We propose TSMH, …