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20122026
most citedScore-Based Generative Modeling through Stochastic Differential Equations

1.3k citations · 2.4k across the 117 of their papers we have counts for

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Showing 2019Show all

30 papers · 1 filter

cs.CV2019

Cloud Removal in Satellite Images Using Spatiotemporal Generative Networks

Vishnu Sarukkai, Anirudh Jain, Burak Uzkent +1

Satellite images hold great promise for continuous environmental monitoring and earth observation. Occlusions cast by clouds, however, can severely limit coverage, making ground in…

cs.CV2019

Efficient Object Detection in Large Images using Deep Reinforcement Learning

Burak Uzkent, Christopher Yeh, Stefano Ermon

Traditionally, an object detector is applied to every part of the scene of interest, and its accuracy and computational cost increases with higher resolution images. However, in so…

cs.CV20194 cited

Approximating Human Judgment of Generated Image Quality

Y. Alex Kolchinski, Sharon Zhou, Shengjia Zhao +2

Generative models have made immense progress in recent years, particularly in their ability to generate high quality images. However, that quality has been difficult to evaluate ri…

cs.LG20195 cited

Approximating the Permanent by Sampling from Adaptive Partitions

Jonathan Kuck, Tri Dao, Hamid Rezatofighi +2

Computing the permanent of a non-negative matrix is a core problem with practical applications ranging from target tracking to statistical thermodynamics. However, this problem is…

cs.LG201932 cited

Meta-Inverse Reinforcement Learning with Probabilistic Context Variables

Lantao Yu, Tianhe Yu, Chelsea Finn +1

Providing a suitable reward function to reinforcement learning can be difficult in many real world applications. While inverse reinforcement learning (IRL) holds promise for automa…

cs.LG201916 cited

Unsupervised Out-of-Distribution Detection with Batch Normalization

Jiaming Song, Yang Song, Stefano Ermon

Likelihood from a generative model is a natural statistic for detecting out-of-distribution (OoD) samples. However, generative models have been shown to assign higher likelihood to…