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Qianru Sun3
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Looking to listen at the cocktail party a speaker-independent audio-visual model for speech separation - SIGGRAPH 2018 ARIEL EPHRAT, Google Research and The Hebrew University of Jerusalem, Israel INBAR MOSSERI, Google Research
 ORAN LANG, Google Research
 TALI DEKEL, Google Research KEVIN WILSON, Google Research AVINATAN HASSIDIM, Google Research WILLIAM T. FREEMAN, Google Research MICHAEL RUBINSTEIN, Google Research ͲΜͳ΋ͷʁ ઌߦݚڀͱൺ΂ͯͲ͕͍͜͢͝ʁ ٕज़΍ख๏ͷΩϞ͸Ͳ͜ʁ ٞ࿦͸͋Δʁ ࣍ʹಡΉ΂͖࿦จ͸ʁ ෳ਺ͷ࿩ऀ͔Βɼը૾ͱԻ੠Λ΋ͱʹϑΟϧλΛ࡞੒ ͠ɼ֤ʑͷԻ੠Λநग़Ͱ͖Δɽ "741&&$)
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GQT ͱ45'5 TIPSU
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ଞͷख๏Ͱ͸࿩ऀ͝ͱʹಠཱͨ͠σʔληοτΛ༻͍͍ͯͨʹ ΋͔͔ΘΒͣɼຊख๏ͷ΄͏্͕ճͬͨɽ إͷಈ͖͕ͲΕ͚ͩد༩͔ͨ͠෼ੳͨ͠ɽޱҎ֎΋ॏ ཁΒ͍͠ɽ David F. Harwath, Antonio Torralba, and James R. Glass. 2016. Unsupervised Learning of Spoken Language with Visual Context. In NIPS. 
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Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks - PMLR 2017 ARIEL EPHRAT, Google Research and The Hebrew University of Jerusalem, Israel INBAR MOSSERI, Google Research
 ORAN LANG, Google Research
 TALI DEKEL, Google Research KEVIN WILSON, Google Research AVINATAN HASSIDIM, Google Research WILLIAM T. FREEMAN, Google Research MICHAEL RUBINSTEIN, Google Research ͲΜͳ΋ͷʁ ઌߦݚڀͱൺ΂ͯͲ͕͍͜͢͝ʁ ٕज़΍ख๏ͷΩϞ͸Ͳ͜ʁ ٞ࿦͸͋Δʁ ࣍ʹಡΉ΂͖࿦จ͸ʁ ޯ഑߱Լ๏Λ࢖͍ͬͯΔ͢΂ͯͷख๏ʹ࢖͑ΔNFUB MFBSOJOHख๏.".-ͷఏҊɽ Ϟσϧ΍ύϥϝʔλʹ੍໿ΛՃ͑ͳ͍͍ͯ͘ɽ λεΫू߹ʹ͓͍ͯ'JOF
5VOJOH͢Δͱ͍͍஋ʹߦ͘Α͏ͳॳ ظ஋Λֶशɽ Ͳ͏΍ͬͯ༗ޮͩͱݕূͨ͠ʁ ճؼ

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ΑΓૣֶ͘शՄೳ ϚϧνλεΫʹର͢ΔॳظԽΛਂ૚ֶश΍ڧԽֶशͷ ඪ४తͳཁૉͱ͢Δ͜ͱ͕͜Ε͔ΒॏཁʹͳΓͦ͏ɽ Al-Shedivat, Maruan, et al. "Continuous adaptation via meta- learning in nonstationary and competitive environments." arXiv preprint arXiv:1710.03641 (2017). 
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Deep Image Prior - CVPR 2018 Dmitry Ulyanov Skolkovo Institute of Science and Technology, Yandex Andrea Vedaldi University of Oxford [email protected] Victor Lempitsky Skolkovo Institute of Science and Technology (Skoltech) [email protected] ͲΜͳ΋ͷʁ ઌߦݚڀͱൺ΂ͯͲ͕͍͜͢͝ʁ ٕज़΍ख๏ͷΩϞ͸Ͳ͜ʁ ٞ࿦͸͋Δʁ ࣍ʹಡΉ΂͖࿦จ͸ʁ ʮը૾ͱ͸͜͏͍͏΋ͷʯͱ͍͏ࣄલ৘ใ͕$//ͷߏ଄ࣗ ମʹͦ΋ͦ΋උΘ͍ͬͯΔͱԾఆ͠ɼ୯Ұը૾ͷΈΛ༻͍ͨ ֶशͰɼͦͷը૾ͷEFOPJTJOH
IJHI
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JOQBJOUͰ͸ $//ͷߏ଄্ɼ("/ͱಉ༷ɼ֨ࢠঢ়ʹͳΓ΍͍͢ʁ [24] V. Papyan, Y. Romano, and M. Elad. Convolutional neural networks analyzed via convolutional sparse coding. Journal of Machine Learning Research, 18(83):1–52, 2017. 
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A Neural Representation of Sketch Drawings - arXiv 2017 David Ha Google Brain [email protected] Douglas Eck Google Brain [email protected] ͲΜͳ΋ͷʁ ઌߦݚڀͱൺ΂ͯͲ͕͍͜͢͝ʁ ٕज़΍ख๏ͷΩϞ͸Ͳ͜ʁ ٞ࿦͸͋Δʁ ࣍ʹಡΉ΂͖࿦จ͸ʁ 3//ͰεέονΛඳ͘ɽ
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Toward Multimodal Image-to-Image Translation - NIPS 2017 Jun-Yan Zhu UC Berkeley Trevor Darrell UC Berkeley Richard Zhang UC Berkeley Alexei A. Efros Oliver Wang Deepak Pathak UC Berkeley Eli Shechtman Adobe Research UC Berkeley Adobe Research ͲΜͳ΋ͷʁ ઌߦݚڀͱൺ΂ͯͲ͕͍͜͢͝ʁ ٕज़΍ख๏ͷΩϞ͸Ͳ͜ʁ ٞ࿦͸͋Δʁ ࣍ʹಡΉ΂͖࿦จ͸ʁ ը૾ͷը෩ม׵ΛύλʔϯͰ͸ͳ͘ෳ਺Ͱ͖Δɽ QJYQJYͰ͸ੜ੒࣌ʹ༩͑ΔTFFEϊΠζΛ޻෉ͯ͠΋ NPEF
DPMMBQTFͯ͠͠·͕ͬͨɼ͠ͳ͘ͳͬͨɽ D7"&("/ͱD-3("/Λ·ͱΊͨɼ#JDZDMF("/ͱ͍͏Ϟσ ϧɽ Ͳ͏΍ͬͯ༗ޮͩͱݕূͨ͠ʁ edges → photos , Google maps → satellite, labels → images, and outdoor night → day images ͷม׵Λpix2pix+noise, cAE-GAN, cVAE-GAN, cVAE-GAN++, cLR-GAN, BicycleGAN Ͱ΍ͬͯΈͨɽGoogle maps → satellites ͰLPIPSͱ͍͏ଟ༷ੑΛଌΔείΞΛൺֱɽ Amazon ϝΧχΧϧλʔΫͰὃ͞Εͨ཰Λൺֱɽ ଟ༷ੑΛଌΔ-1*14ͱ͍͏ࢦඪͷείΞ͸ը૾͕ෆࣗવͳͱ͖΋ ߴ͘ͳΔɽ
MBUFOUͷ࣍ݩ͸গͳ͗͢ΔͱNPEF
DPMMBQTF͢Δ͕ɼଟ͗͢Δͱ ΑΓଟ͘ͷ৘ใྔΛ࣋ͬͯ͠·͏ͨΊྑ͘ͳ͍ɽ • A. B. L. Larsen, S. K. Sønderby, H. Larochelle, and O. Winther. Autoencoding beyond pixels using a learned similarity metric. In ICML, 2016. 
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Autoencoding beyond pixels using a learned similarity metric - ICML 2016 Anders Boesen Lindbo Larsen1 Søren Kaae Sønderby2 Hugo Larochelle3 Ole Winther1,2 1 Department for Applied Mathematics and Computer Science, Technical University of Denmark 2 Bioinformatics Centre, Department of Biology, University of Copenhagen, Denmark 3 Twitter, Cambridge, MA, USA ͲΜͳ΋ͷʁ 7"&ͱ("/Λ૊Έ߹Θͤͨɽ("/ͷEJTDSJNJOBUPSͰ ֶश͞Εͨಛ௃දݱΛ7"&ͷPCKFDUJWFʹ࢖༻Ͱ͖Δɽ 
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 Vincent Dumoulin1, Ishmael Belghazi1, Ben Poole2
 Olivier Mastropietro1, Alex Lamb1, Martin Arjovsky3
 Aaron Courville1†
 1 MILA, Université de Montréal, fi[email protected].
 2 Neural Dynamics and Computation Lab, Stanford, [email protected]. 3 New York University, [email protected]. †CIFAR Fellow. ͲΜͳ΋ͷʁ Y͔Β(FOFSBUPSʹΑͬͯਪ࿦ͨ͠[ͱɼ[͔Β (FOFSBUPSʹΑͬͯਪ࿦ͨ͠ϖΞಉ࢜Λ%JTDSJNJOBUPS ʹΑͬͯൺ΂Δɽ ADVERSARIALLY LEARNED INFERENCE - ICLR 2017 

InfoGAN: Interpretable Representation Learning by Information Maximizing Generative Adversarial Nets - NIPS 2016 • X. Chen, Y. Duan, R. Houthooft, J. Schulman, I. Sutskever, and P. Abbeel. ͲΜͳ΋ͷʁ ڭࢣͳֶ͠शͰੜ੒ը૾Λ੍ޚͰ͖Δ
જࡏม਺ͱ؍࡯ͷؒͷ૬ޓ৘ใྔΛ࠷େԽ͢Δ 
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 • R. Zhang, J.-Y. Zhu, P. Isola, X. Geng, A. S. Lin, T. Yu, and A. A. Efros. ͲΜͳ΋ͷʁ നࠇࣸਅΛϦΞϧλΠϜͰண৭Ͱ͖ΔɽϢʔβʔΠϯ ϓοτܕͱσʔλυϦϒϯܕͷண৭ख๏ͷ༥߹ɽ
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 Real-Time User-Guided Image Colorization with Learned Deep Priors - SIGGRAPH 2017 

CartoonGAN: Generative Adversarial Networks for Photo Cartoonization - CVPR 2018 Yang Chen Tsinghua University, China Yu-Kun Lai Cardiff University, UK [email protected] Yong-Jin Liu∗ Tsinghua University, China ͲΜͳ΋ͷʁ ઌߦݚڀͱൺ΂ͯͲ͕͍͜͢͝ʁ ٕज़΍ख๏ͷΩϞ͸Ͳ͜ʁ ٞ࿦͸͋Δʁ ࣍ʹಡΉ΂͖࿦จ͸ʁ ࣸਅΛອը෩ʹม׵͢Δ$BSUPPO("/ΛఏҊɽ ରσʔλ͕ඞཁͳ͍ɽ ଛࣦؔ਺ʹɼ௨ৗͷࣝผଛࣦʹՃ͑ͯɼֶशࡁΈ7((͔Βͷग़ ྗΛ༻͍ͯ(͕ੜ੒͢ΔֆͷҙຯΛࣦΘͳ͍Α͏͢Δϩε  ͱɼ ΤοδΛࡍཱͨͤΔϩε ී௨ͷࣸਅ͔ɼΤοδΛऔΓআ͍ͨ ອը͔ɼΤοδͦͷ··ͷອը͔ɼΛࣝผ Λ࡞ͬͨ Ͳ͏΍ͬͯ༗ޮͩͱݕূͨ͠ʁ ৽ւ੣෩ɼٶ࡚ॣ෩ͳͲʹม׵ɽNSTɼCycleGAN౳ͱൺֱɽ ΑΓອըͬΆ͘ɼΤοδ΋ࡍཱͭΑ͏ʹͳͬͨɽ কདྷతʹਓ෺ը΍ɼಈըʹ΋ద༻͍ͨ͠ɽ • [38] J.-Y.Zhu,T.Park,P.Isola,andA.A.Efros. Unpairedimage- to-image translation using cycle-consistent adversarial net- works. In International Conference on Computer Vision, 2017. 
 • [6] L. Gatys, A. Ecker, and M. Bethge. Image style transfer using convolutional neural networks. In IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pages 2414–2423, 2016. 
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Unpairedimage- to-image translation using cycle-consistent adversarial net- works. - ICCV 2017 J.-Y.Zhu,T.Park,P.Isola,andA.A.Efros. ͲΜͳ΋ͷʁ $ZDMF("/
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 L. Gatys, A. Ecker, and M. Bethge. ͲΜͳ΋ͷʁ 7((ͰऔΓग़ͨ͠ϨΠϠʔ͝ͱͷTUZMFදݱͱDPOUFOU දݱΛݩʹɼͦΕͧΕΛอ࣋͢ΔΑ͏ͳϩεؔ਺Λ࡞ Γɼը෩ม׵͢Δɽ Image style transfer using convolutional neural networks - CVPR 2016 

Rectifier nonlinearities improve neural network acoustic models . - ICML 2013 A. L. Maas, A. Y. Hannun, and A. Y. Ng. ͲΜͳ΋ͷʁ -FBLZ3F-6ͷఏҊɽ
Ի੠ೝࣝγεςϜͰTJHNPJEܥͳͲͱൺֱͯ͠ˋྑ͘ ͳͬͨɽ 
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 • Y. Chen, Y.-K. Lai, and Y.-J. Liu. ͲΜͳ΋ͷʁ άϨΠεέʔϧͰɼࣸਅΛອը෩ʹม׵͢Δɽ
(BUZͷٕज़Λ୯७ʹອըʹ࢖༻ͨ͠ͷʹՃ͑ͯɼࣸਅ ͔ອըՈΛࣝผ͢ΔΑ͏ʹϩεΛՃ͑ͨɽ Transforming photos to comics using convolutional neural networks. - ICIP 2017 

Visual A ribute Transfer through Deep Image Analogy - TOG 2017 J. Liao, Y. Yao, L. Yuan, G. Hua, and S. B. Kang. ͲΜͳ΋ͷʁ lEFFQ
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Neural scene representation and rendering - Science 2018 June 15 S. M. Ali Eslami*†, Danilo Jimenez Rezende†, Frederic Besse, Fabio Viola,
 Ari S. Morcos, Marta Garnelo, Avraham Ruderman, Andrei A. Rusu, Ivo Danihelka, Karol Gregor, David P. Reichert, Lars Buesing, Theophane Weber, Oriol Vinyals, Dan Rosenbaum, Neil Rabinowitz, Helen King, Chloe Hillier, Matt Botvinick,
 Daan Wierstra, Koray Kavukcuoglu, Demis Hassabis ͲΜͳ΋ͷʁ ઌߦݚڀͱൺ΂ͯͲ͕͍͜͢͝ʁ ٕज़΍ख๏ͷΩϞ͸Ͳ͜ʁ ٞ࿦͸͋Δʁ ࣍ʹಡΉ΂͖࿦จ͸ʁ ෳ਺ͷࢹ఺ͷը૾͔Βɺର৅ͷࡾ࣍ݩੈքΛූ߸Խ͠ ҟͳΔࢹ఺͔ΒͷࢹքΛ෮ݩ͢ΔɻۭؒϞσϧΛજࡏ ม਺ͱ͢ΔજࡏϞσϧͰ࠷దԽ͢Δɻ ਓؒͷϥϕϧ෇ͳͲͷࣄલ஌ࣝແ͠ͰTDFOFΛղऍ͠ɼදݱͰ͖Δɽ
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Conditional image generation with PixelCNN decoders - NIPS 2016 A. van den Oord et al. ͲΜͳ΋ͷʁ લ·ͰͷϐΫηϧ͔Β࣍ͷϐΫηϧΛ༧ଌ͢Δ 1JYFM$//ʹʮ໡఺ CMJOE
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 A. R. Zamir et al. ͲΜͳ΋ͷʁ %0'Χϝϥͷϙʔζਪఆ
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Generic 3D representation via pose estimation and matching - ECCV 2016 

Unsupervised learning of 3D structure from images - NIPS 2016 D. J. Rezende et al ͲΜͳ΋ͷʁ ը૾͔Β%ͷ෺ମΛੜ੒ɽ
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 A. A. Rusu et al ͲΜͳ΋ͷʁ ௿Ϩϕϧͷࢹ֮ಛ௃ΛߴϨϕϧͷϙϦγʔʹҠ͍ͯ͠ ͘QSPHSFTTJWF
OFUXPSLʹΑͬͯγϛϡϨʔγϣϯͰ ͷֶशΛ࣮؀ڥʹҠ͢ɽ
Sim-to-real robot learning from pixels with progressive nets. - arXiv 2016 

Stochastic back-propagation and variational inference in deep latent Gaussian models - ICML 2014 D. J. Rezende, S. Mohamed, D. Wierstra, ͲΜͳ΋ͷʁ Ϟσϧʹࣄલ෼෍Λஔ͍ͯσʔλͷ֬཰తΤϯίʔυ Λ͢Δɽੜ੒ϞσϧͱࣝผϞσϧͰ#BDLQSPQΛ֬཰ ม਺Ͱߦ͏ɽ

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