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ARCHIVEMONTHLY»FEBRUARY2018«
27
th
FEBRUARY2018
READING NOTES
Chris J. Maddison, Andriy Mnih, Yee Whye Teh.
The Concrete Distribution: A Continuous Relaxation of Discrete Random Variables
. CoRR abs/1611.00712 (2016)
DEEP LEARNING
MACHINE LEARNING
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26
th
FEBRUARY2018
READING NOTES
Eric Jang, Shixiang Gu, Ben Poole.
Categorical Reparameterization with Gumbel-Softmax
. CoRR, 2016.
DEEP LEARNING
MACHINE LEARNING
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24
th
FEBRUARY2018
READING NOTES
Daniel Jiwoong Im, Sungjin Ahn, Roland Memisevic, Yoshua Bengio.
Denoising Criterion for Variational Auto-Encoding Framework
. AAAI, 2017.
DEEP LEARNING
MACHINE LEARNING
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22
th
FEBRUARY2018
READING NOTES
Kihyuk Sohn, Honglak Lee, Xinchen Yan.
Learning Structured Output Representation using Deep Conditional Generative Models
. NIPS, 2015.
DEEP LEARNING
MACHINE LEARNING
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21
th
FEBRUARY2018
READING NOTES
Diederik P. Kingma, Shakir Mohamed, Danilo Jimenez Rezende, Max Welling.
Semi-supervised Learning with Deep Generative Models
. NIPS, 2014.
DEEP LEARNING
MACHINE LEARNING
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19
th
FEBRUARY2018
READING NOTES
Moritz Menze, Andreas Geiger.
Object scene flow for autonomous vehicles
. CVPR, 2015.
COMPUTER VISION
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17
th
FEBRUARY2018
READING NOTES
Jifeng Dai, Kaiming He, Jian Sun.
Convolutional feature masking for joint object and stuff segmentation
. CVPR, 2015.
COMPUTER VISION
DEEP LEARNING
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15
th
FEBRUARY2018
READING NOTES
Jonas Uhrig, Marius Cordts, Uwe Franke, Thomas Brox.
Pixel-Level Encoding and Depth Layering for Instance-Level Semantic Labeling
. GCPR, 2016.
COMPUTER VISION
DEEP LEARNING
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11
th
FEBRUARY2018
READING NOTES
Jifeng Dai, Kaiming He, Jian Sun.
Instance-Aware Semantic Segmentation via Multi-task Network Cascades
. CVPR. 2016.
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05
th
FEBRUARY2018
READING NOTES
Elad Hoffer, Itay Hubara, Nir Ailon.
Deep unsupervised learning through spatial contrasting
. CoRR abs/1610.00243, 2016.
COMPUTER VISION
DEEP LEARNING
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