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Probabilistic and Semantic Descriptions of Image Manifolds and Their Applications
6 July 2023
Peter Tu
Zhaoyuan Yang
Leonid Sigal
Zhiwei Xu
Jing Zhang
Yiwei Fu
Dylan Campbell
Jaskirat Singh
Tianyu Wang
DiffM
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Papers citing
"Probabilistic and Semantic Descriptions of Image Manifolds and Their Applications"
30 / 30 papers shown
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Multi-Resolution Continuous Normalizing Flows
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The Intrinsic Dimension of Images and Its Impact on Learning
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Zero-Shot Text-to-Image Generation
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Dual Contradistinctive Generative Autoencoder
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Denoising Diffusion Implicit Models
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Oliver Wang
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Normalizing Flows for Probabilistic Modeling and Inference
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Eric T. Nalisnick
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S. Mohamed
Balaji Lakshminarayanan
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Normalizing Flows: An Introduction and Review of Current Methods
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Marcus A. Brubaker
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25 Aug 2019
Geometry-Aware Maximum Likelihood Estimation of Intrinsic Dimension
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N. Mokrov
Maxim Panov
Y. Yanovich
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12 Apr 2019
Glow: Generative Flow with Invertible 1x1 Convolutions
Diederik P. Kingma
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Exploring Disentangled Feature Representation Beyond Face Identification
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Fangyin Wei
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Junjie Yan
Xiaogang Wang
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Isolating Sources of Disentanglement in Variational Autoencoders
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Xuechen Li
Roger C. Grosse
David Duvenaud
DRL
61
447
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Adversarial Patch
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Dandelion Mané
Aurko Roy
Martín Abadi
Justin Gilmer
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Fashion-MNIST: a Novel Image Dataset for Benchmarking Machine Learning Algorithms
Han Xiao
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Roland Vollgraf
285
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Towards Deep Learning Models Resistant to Adversarial Attacks
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Aleksandar Makelov
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Emergence of Language with Multi-agent Games: Learning to Communicate with Sequences of Symbols
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Alexey Kurakin
Nicolas Papernot
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177
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Towards Evaluating the Robustness of Neural Networks
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268
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Variational Inference with Normalizing Flows
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S. Mohamed
DRL
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318
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FaceNet: A Unified Embedding for Face Recognition and Clustering
Florian Schroff
Dmitry Kalenichenko
James Philbin
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Deep Learning Face Attributes in the Wild
Ziwei Liu
Ping Luo
Xiaogang Wang
Xiaoou Tang
CVBM
247
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Auto-Encoding Variational Bayes
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