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Chaoyun Zhang, Xi Ouyang, and Paul Patras

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1 Chaoyun Zhang, Xi Ouyang, and Paul Patras
ZipNet-GAN: Inferring Fine-grained Mobile Traffic Patterns via a Generative Adversarial Neural Network Chaoyun Zhang, Xi Ouyang, and Paul Patras Huazhong University of Science and Technology University of Edinburgh

2 The Goal of Mobile Traffic Analysis
1. Social analysis -- Traffic and social features User's interactions Demographic research Chaoyun Zhang et al ZipNet-GAN December 14, 2017 Chaoyun Zhang et al ZipNet-GAN December 01, 2017 Chaoyun Zhang et al ZipNet-GAN November 16, 2017 Chaoyun Zhang et al ZipNet-GAN November 30, 2017

3 The Goal of Mobile Traffic Analysis
1. Social analysis -- Traffic and social features User's interactions Demographic research 2. Mobility analysis -- Traffic and users' mobility Movement prediction Transportation planning Chaoyun Zhang et al ZipNet-GAN December 14, 2017 Chaoyun Zhang et al ZipNet-GAN December 01, 2017 Chaoyun Zhang et al ZipNet-GAN November 16, 2017 Chaoyun Zhang et al ZipNet-GAN November 30, 2017

4 The Goal of Mobile Traffic Analysis
1. Social analysis -- Traffic and social features User's interactions Demographic research 2. Mobility analysis -- Traffic and users' mobility Movement prediction Transportation planning 3. Network analysis -- Traffic and network condition Resource allocation Fault diagnosis Chaoyun Zhang et al ZipNet-GAN December 14, 2017 Chaoyun Zhang et al ZipNet-GAN December 01, 2017 Chaoyun Zhang et al ZipNet-GAN November 16, 2017 Chaoyun Zhang et al ZipNet-GAN November 30, 2017

5 The Goal of Mobile Traffic Analysis
1. Social analysis -- Traffic and social features User's interactions Demographic research 2. Mobility analysis -- Traffic and users' mobility Movement prediction Transportation planning 3. Network analysis -- Traffic and network condition Resource allocation Fault diagnosis Require fine-grained knowledge of mobile traffic !!! Chaoyun Zhang et al ZipNet-GAN December 14, 2017 Chaoyun Zhang et al ZipNet-GAN November 16, 2017 Chaoyun Zhang et al ZipNet-GAN December 01, 2017 Chaoyun Zhang et al ZipNet-GAN November 30, 2017

6 Fine-Grained Traffic Measurement
1. Relies on dedicated probes Packet Gateway (PGW) probes -- yield approximated position Chaoyun Zhang et al ZipNet-GAN December 14, 2017 Chaoyun Zhang et al ZipNet-GAN December 01, 2017 Chaoyun Zhang et al ZipNet-GAN November 16, 2017 Chaoyun Zhang et al ZipNet-GAN November 30, 2017

7 Fine-Grained Traffic Measurement
1. Relies on dedicated probes Packet Gateway (PGW) probes -- yield approximated position Radio Network Controller (RNC) probes -- have small geographical coverage Chaoyun Zhang et al ZipNet-GAN December 14, 2017 Chaoyun Zhang et al ZipNet-GAN December 01, 2017 Chaoyun Zhang et al ZipNet-GAN November 16, 2017 Chaoyun Zhang et al ZipNet-GAN November 30, 2017

8 Fine-Grained Traffic Measurement
1. Relies on dedicated probes , Packet Gateway (PGW) probes -- yield approximated position Radio Network Controller (RNC) probes -- have small geographical coverage 2. Involves data post-processing overhead Call detail record reports transfer Data storage Spatial aggregation Chaoyun Zhang et al ZipNet-GAN December 14, 2017 Chaoyun Zhang et al ZipNet-GAN December 01, 2017 Chaoyun Zhang et al ZipNet-GAN November 16, 2017 Chaoyun Zhang et al ZipNet-GAN November 30, 2017

9 Coarse-Grained to Fine-Grained
Fine-grain traffic measurement (desired) Chaoyun Zhang et al ZipNet-GAN December 14, 2017 Chaoyun Zhang et al ZipNet-GAN December 01, 2017 Chaoyun Zhang et al ZipNet-GAN November 16, 2017 Chaoyun Zhang et al ZipNet-GAN November 30, 2017

10 Coarse-Grained to Fine-Grained
Aggregation Coarse-grain traffic measurement (Aggregated) Fine-grain traffic measurement (desired) Chaoyun Zhang et al ZipNet-GAN December 14, 2017 Chaoyun Zhang et al ZipNet-GAN December 01, 2017 Chaoyun Zhang et al ZipNet-GAN November 16, 2017 Chaoyun Zhang et al ZipNet-GAN November 30, 2017

11 Coarse-Grained to Fine-Grained
? Costly! Coarse-grain traffic measurement (Aggregated) Fine-grain traffic measurement (desired) Chaoyun Zhang et al ZipNet-GAN December 14, 2017 Chaoyun Zhang et al ZipNet-GAN December 01, 2017 Chaoyun Zhang et al ZipNet-GAN November 16, 2017 Chaoyun Zhang et al ZipNet-GAN November 30, 2017

12 Coarse-Grained to Fine-Grained
? Machine Learning? Coarse-grain traffic measurement (Aggregated) Fine-grain traffic measurement (desired) Chaoyun Zhang et al ZipNet-GAN December 14, 2017 Chaoyun Zhang et al ZipNet-GAN December 01, 2017 Chaoyun Zhang et al ZipNet-GAN November 16, 2017 Chaoyun Zhang et al ZipNet-GAN November 30, 2017

13 Mobile Traffic Super-Resolution (MTSR)
* Image source: Chaoyun Zhang et al ZipNet-GAN December 14, 2017 Chaoyun Zhang et al ZipNet-GAN December 01, 2017 Chaoyun Zhang et al ZipNet-GAN November 16, 2017 Chaoyun Zhang et al ZipNet-GAN November 30, 2017

14 Mobile Traffic Super-Resolution (MTSR)
* Image source: Chaoyun Zhang et al ZipNet-GAN December 14, 2017 Chaoyun Zhang et al ZipNet-GAN December 01, 2017 Chaoyun Zhang et al ZipNet-GAN November 16, 2017 Chaoyun Zhang et al ZipNet-GAN November 30, 2017

15 Mobile Traffic Super-Resolution (MTSR)
Both learn the correlation between low-resolution and high-resolution “frames”! * Image source: Chaoyun Zhang et al ZipNet-GAN December 14, 2017 Chaoyun Zhang et al ZipNet-GAN November 16, 2017 Chaoyun Zhang et al ZipNet-GAN December 01, 2017 Chaoyun Zhang et al ZipNet-GAN November 30, 2017

16 Mobile Traffic Super-Resolution (MTSR)
Inspiration: Apply image SR techniques to the MTSR ! * Image source: Chaoyun Zhang et al ZipNet-GAN December 14, 2017 Chaoyun Zhang et al ZipNet-GAN November 16, 2017 Chaoyun Zhang et al ZipNet-GAN December 01, 2017 Chaoyun Zhang et al ZipNet-GAN November 30, 2017

17 Solution: Generative Adversarial Nets (GANs)
1. An unsupervised deep learning framework. S S Chaoyun Zhang et al ZipNet-GAN December 14, 2017 Chaoyun Zhang et al ZipNet-GAN December 01, 2017 Chaoyun Zhang et al ZipNet-GAN November 16, 2017 Chaoyun Zhang et al ZipNet-GAN November 30, 2017

18 Generative Adversarial Nets (GANs)
Solution: Generative Adversarial Nets (GANs) Generative Adversarial Nets (GANs) 1. An unsupervised deep learning framework. 2. Learn the target distribution and generate artificial data. S S Chaoyun Zhang et al ZipNet-GAN December 14, 2017 Chaoyun Zhang et al ZipNet-GAN December 01, 2017 Chaoyun Zhang et al ZipNet-GAN November 16, 2017 Chaoyun Zhang et al ZipNet-GAN November 30, 2017

19 Generative Adversarial Nets (GANs)
Solution: Generative Adversarial Nets (GANs) Generative Adversarial Nets (GANs) 1. An unsupervised deep learning framework. 2. Learn the target distribution and generate artificial data. 3. Force the output of the model to be closer to real data distributions. Chaoyun Zhang et al ZipNet-GAN December 14, 2017 Chaoyun Zhang et al ZipNet-GAN December 01, 2017 Chaoyun Zhang et al ZipNet-GAN November 16, 2017 Chaoyun Zhang et al ZipNet-GAN November 30, 2017

20 ZipNet-GAN ZipNet-GAN The Generator (ZipNet)
The Discriminator (VGG-net) Chaoyun Zhang et al ZipNet-GAN December 14, 2017 Chaoyun Zhang et al ZipNet-GAN November 16, 2017 Chaoyun Zhang et al ZipNet-GAN December 01, 2017 Chaoyun Zhang et al ZipNet-GAN November 30, 2017

21 ZipNet-GAN ZipNet-GAN The Generator (ZipNet)
The Discriminator (VGG-net) Chaoyun Zhang et al ZipNet-GAN December 14, 2017 Chaoyun Zhang et al ZipNet-GAN November 16, 2017 Chaoyun Zhang et al ZipNet-GAN December 01, 2017 Chaoyun Zhang et al ZipNet-GAN November 30, 2017

22 ZipNet-GAN ZipNet-GAN The Generator (ZipNet)
The Discriminator (VGG-net) Chaoyun Zhang et al ZipNet-GAN December 14, 2017 Chaoyun Zhang et al ZipNet-GAN November 16, 2017 Chaoyun Zhang et al ZipNet-GAN December 01, 2017 Chaoyun Zhang et al ZipNet-GAN November 30, 2017

23 ZipNet-GAN ZipNet-GAN The Generator (ZipNet)
The Discriminator (VGG-net) Chaoyun Zhang et al ZipNet-GAN December 14, 2017 Chaoyun Zhang et al ZipNet-GAN November 16, 2017 Chaoyun Zhang et al ZipNet-GAN December 01, 2017 Chaoyun Zhang et al ZipNet-GAN November 30, 2017

24 ZipNet-GAN ZipNet-GAN The Generator (ZipNet)
The Discriminator (VGG-net) Chaoyun Zhang et al ZipNet-GAN December 14, 2017 Chaoyun Zhang et al ZipNet-GAN November 16, 2017 Chaoyun Zhang et al ZipNet-GAN December 01, 2017 Chaoyun Zhang et al ZipNet-GAN November 30, 2017

25 Dataset Dataset Released by Telecom Italia's Big Data Challenge
Chaoyun Zhang et al ZipNet-GAN December 14, 2017 Chaoyun Zhang et al ZipNet-GAN November 16, 2017 Chaoyun Zhang et al ZipNet-GAN December 01, 2017 Chaoyun Zhang et al ZipNet-GAN November 30, 2017

26 Dataset Dataset Released by Telecom Italia's Big Data Challenge
Measurement of mobile traffic volume between 1 Nov 2013 and 1 Jan 2014 in Milan. Chaoyun Zhang et al ZipNet-GAN December 14, 2017 Chaoyun Zhang et al ZipNet-GAN November 16, 2017 Chaoyun Zhang et al ZipNet-GAN December 01, 2017 Chaoyun Zhang et al ZipNet-GAN November 30, 2017

27 Dataset Dataset Released by Telecom Italia's Big Data Challenge
Measurement of mobile traffic volume between 1 Nov 2013 and 1 Jan 2014 in Milan. Aggregated every 10 minutes. Chaoyun Zhang et al ZipNet-GAN December 14, 2017 Chaoyun Zhang et al ZipNet-GAN November 16, 2017 Chaoyun Zhang et al ZipNet-GAN December 01, 2017 Chaoyun Zhang et al ZipNet-GAN November 30, 2017

28 Dataset Dataset Released by Telecom Italia's Big Data Challenge
Measurement of mobile traffic volume between 1 Nov 2013 and 1 Jan 2014 in Milan. Aggregated every 10 minutes. Partitioned in 100×100 grids. Chaoyun Zhang et al ZipNet-GAN December 14, 2017 Chaoyun Zhang et al ZipNet-GAN November 16, 2017 Chaoyun Zhang et al ZipNet-GAN December 01, 2017 Chaoyun Zhang et al ZipNet-GAN November 30, 2017

29 Four MTSR Instances Chaoyun Zhang et al ZipNet-GAN December 14, 2017 Chaoyun Zhang et al ZipNet-GAN December 01, 2017 Chaoyun Zhang et al ZipNet-GAN November 16, 2017 Chaoyun Zhang et al ZipNet-GAN November 30, 2017

30 Four MTSR Instances Four MTSR Instances Green: 10×10 Probes
Yellow: 4×4 Probes Red: 2×2 Probes Chaoyun Zhang et al ZipNet-GAN December 14, 2017 Chaoyun Zhang et al ZipNet-GAN December 01, 2017 Chaoyun Zhang et al ZipNet-GAN November 16, 2017 Chaoyun Zhang et al ZipNet-GAN November 30, 2017

31 Methods for Comparison
Interpolations Uniform Interpolation (Used by operators) Bicubic Interpolation Chaoyun Zhang et al ZipNet-GAN December 14, 2017 Chaoyun Zhang et al ZipNet-GAN December 01, 2017 Chaoyun Zhang et al ZipNet-GAN November 16, 2017 Chaoyun Zhang et al ZipNet-GAN November 30, 2017

32 Methods for Comparison
Interpolations Uniform Interpolation (Used by operators) Bicubic Interpolation 2. Image Super-Resolution Sparse Coding (SC) Adjusted Anchored Neighborhood Regression (A+) Chaoyun Zhang et al ZipNet-GAN December 14, 2017 Chaoyun Zhang et al ZipNet-GAN December 01, 2017 Chaoyun Zhang et al ZipNet-GAN November 16, 2017 Chaoyun Zhang et al ZipNet-GAN November 30, 2017

33 Methods for Comparison
Interpolations Uniform Interpolation (Used by operators) Bicubic Interpolation 2. Image Super-Resolution Sparse Coding (SC) Adjusted Anchored Neighborhood Regression (A+) 3. Deep Learning Super-Resolution Convolutional Neural Network (SRCNN) ZipNet ZipNet-GAN Chaoyun Zhang et al ZipNet-GAN December 14, 2017 Chaoyun Zhang et al ZipNet-GAN December 01, 2017 Chaoyun Zhang et al ZipNet-GAN November 16, 2017 Chaoyun Zhang et al ZipNet-GAN November 30, 2017

34 Methods for Comparison
Interpolations Uniform Interpolation (Used by operators) Bicubic Interpolation 2. Image Super-Resolution Sparse Coding (SC) Adjusted Anchored Neighborhood Regression (A+) 3. Deep Learning Super-Resolution Convolutional Neural Network (SRCNN) ZipNet ZipNet-GAN Train on data collected in 40 days, validate on 10 days, test on 10 days. Chaoyun Zhang et al ZipNet-GAN December 14, 2017 Chaoyun Zhang et al ZipNet-GAN November 16, 2017 Chaoyun Zhang et al ZipNet-GAN December 01, 2017 Chaoyun Zhang et al ZipNet-GAN November 30, 2017

35 Numerical Results Results Normalised Root Mean Square Error:
The prediction accuracy. Chaoyun Zhang et al ZipNet-GAN December 14, 2017 Chaoyun Zhang et al ZipNet-GAN December 01, 2017 Chaoyun Zhang et al ZipNet-GAN November 16, 2017 Chaoyun Zhang et al ZipNet-GAN November 30, 2017

36 Numerical Results Results Normalised Root Mean Square Error:
The prediction accuracy. Chaoyun Zhang et al ZipNet-GAN December 14, 2017 Chaoyun Zhang et al ZipNet-GAN December 01, 2017 Chaoyun Zhang et al ZipNet-GAN November 16, 2017 Chaoyun Zhang et al ZipNet-GAN November 30, 2017

37 Numerical Results Results Normalised Root Mean Square Error:
The prediction accuracy. Peak Signal-to-Noise Ratio: The quality of reconstruction. Chaoyun Zhang et al ZipNet-GAN December 14, 2017 Chaoyun Zhang et al ZipNet-GAN November 16, 2017 Chaoyun Zhang et al ZipNet-GAN December 01, 2017 Chaoyun Zhang et al ZipNet-GAN November 30, 2017

38 Numerical Results Results Normalised Root Mean Square Error:
The prediction accuracy. Peak Signal-to-Noise Ratio: The quality of reconstruction. Chaoyun Zhang et al ZipNet-GAN December 14, 2017 Chaoyun Zhang et al ZipNet-GAN November 16, 2017 Chaoyun Zhang et al ZipNet-GAN December 01, 2017 Chaoyun Zhang et al ZipNet-GAN November 30, 2017

39 Numerical Results Results Normalised Root Mean Square Error:
The prediction accuracy Peak Signal-to-Noise Ratio: The quality of reconstruction. Structural Similarity: The similarity between frames. Chaoyun Zhang et al ZipNet-GAN December 14, 2017 Chaoyun Zhang et al ZipNet-GAN November 16, 2017 Chaoyun Zhang et al ZipNet-GAN December 01, 2017 Chaoyun Zhang et al ZipNet-GAN November 30, 2017

40 Numerical Results Results 78% lower reconstruction error,
Enhance the resolution of mobile traffic measurements by 100×. 78% lower reconstruction error, 40% higher fidelity of reconstruction patterns, 36.4× structural similarity! Chaoyun Zhang et al ZipNet-GAN December 14, 2017 Chaoyun Zhang et al ZipNet-GAN November 16, 2017 Chaoyun Zhang et al ZipNet-GAN December 01, 2017 Chaoyun Zhang et al ZipNet-GAN November 30, 2017

41 MTSR Examples (Up-10) Chaoyun Zhang et al ZipNet-GAN December 14, 2017 Chaoyun Zhang et al ZipNet-GAN December 01, 2017 Chaoyun Zhang et al ZipNet-GAN November 16, 2017 Chaoyun Zhang et al ZipNet-GAN November 30, 2017

42 MTSR Examples (Up-10) Chaoyun Zhang et al ZipNet-GAN December 14, 2017 Chaoyun Zhang et al ZipNet-GAN December 01, 2017 Chaoyun Zhang et al ZipNet-GAN November 16, 2017 Chaoyun Zhang et al ZipNet-GAN November 30, 2017

43 MTSR Examples (Up-10) Chaoyun Zhang et al ZipNet-GAN December 14, 2017 Chaoyun Zhang et al ZipNet-GAN December 01, 2017 Chaoyun Zhang et al ZipNet-GAN November 16, 2017 Chaoyun Zhang et al ZipNet-GAN November 30, 2017

44 MTSR Examples (Up-10) Chaoyun Zhang et al ZipNet-GAN December 14, 2017 Chaoyun Zhang et al ZipNet-GAN December 01, 2017 Chaoyun Zhang et al ZipNet-GAN November 16, 2017 Chaoyun Zhang et al ZipNet-GAN November 30, 2017

45 MTSR Examples (Up-10) Chaoyun Zhang et al ZipNet-GAN December 14, 2017 Chaoyun Zhang et al ZipNet-GAN December 01, 2017 Chaoyun Zhang et al ZipNet-GAN November 16, 2017 Chaoyun Zhang et al ZipNet-GAN November 30, 2017

46 Impacts of the GAN Chaoyun Zhang et al ZipNet-GAN December 14, 2017 Chaoyun Zhang et al ZipNet-GAN December 01, 2017 Chaoyun Zhang et al ZipNet-GAN November 16, 2017 Chaoyun Zhang et al ZipNet-GAN November 30, 2017

47 Operating with Anomalous Traffic Working with Anomaly
Chaoyun Zhang et al ZipNet-GAN December 14, 2017 Chaoyun Zhang et al ZipNet-GAN December 01, 2017 Chaoyun Zhang et al ZipNet-GAN November 16, 2017 Chaoyun Zhang et al ZipNet-GAN November 30, 2017

48 Operating with Anomalous Traffic Working with Anomaly
Chaoyun Zhang et al ZipNet-GAN December 14, 2017 Chaoyun Zhang et al ZipNet-GAN December 01, 2017 Chaoyun Zhang et al ZipNet-GAN November 16, 2017 Chaoyun Zhang et al ZipNet-GAN November 30, 2017

49 Operating with Anomalous Traffic Working with Anomaly
Chaoyun Zhang et al ZipNet-GAN December 14, 2017 Chaoyun Zhang et al ZipNet-GAN December 01, 2017 Chaoyun Zhang et al ZipNet-GAN November 16, 2017 Chaoyun Zhang et al ZipNet-GAN November 30, 2017

50 Operating with Anomalous Traffic Working with Anomaly
Can operate under anomalous traffic situations ! Chaoyun Zhang et al ZipNet-GAN December 14, 2017 Chaoyun Zhang et al ZipNet-GAN December 01, 2017 Chaoyun Zhang et al ZipNet-GAN November 16, 2017 Chaoyun Zhang et al ZipNet-GAN November 30, 2017

51 Summary Mobile traffic analysis requires fine-grained knowledge 1
Measuring mobile traffic in fine granularity is costly 2 Solution: Mobile Traffic Super-Resolution (MTSR) 3 Chaoyun Zhang et al ZipNet-GAN December 14, 2017 Chaoyun Zhang et al ZipNet-GAN December 01, 2017 Chaoyun Zhang et al ZipNet-GAN November 16, 2017 Chaoyun Zhang et al ZipNet-GAN November 30, 2017

52 Summary Summary Mobile traffic analysis requires fine-grained knowledge 1 Measuring mobile traffic with fine granularity is costly 2 Solution: Mobile Traffic Super-Resolution (MTSR) 3 Chaoyun Zhang et al ZipNet-GAN December 14, 2017 Chaoyun Zhang et al ZipNet-GAN December 01, 2017 Chaoyun Zhang et al ZipNet-GAN November 16, 2017 Chaoyun Zhang et al ZipNet-GAN November 30, 2017

53 Summary Summary Mobile traffic analysis requires fine-grained knowledge 1 Measuring mobile traffic with fine granularity is costly 2 Solution: Mobile Traffic Super-Resolution (MTSR) 3 Chaoyun Zhang et al ZipNet-GAN December 14, 2017 Chaoyun Zhang et al ZipNet-GAN December 01, 2017 Chaoyun Zhang et al ZipNet-GAN November 16, 2017 Chaoyun Zhang et al ZipNet-GAN November 30, 2017

54 Summary Summary Mobile traffic analysis requires fine-grained knowledge 1 Measuring mobile traffic with fine granularity is costly 2 Solution: Mobile Traffic Super-Resolution (MTSR) 3 ZipNet + GAN Improve the granularity of traffic snapshot by up to 100× Outperform other interpolation approaches Work well with anomaly traffic Chaoyun Zhang et al ZipNet-GAN December 14, 2017 Chaoyun Zhang et al ZipNet-GAN November 16, 2017 Chaoyun Zhang et al ZipNet-GAN December 01, 2017 Chaoyun Zhang et al ZipNet-GAN November 30, 2017

55 Summary Summary Mobile traffic analysis requires fine-grained knowledge 1 Measuring mobile traffic with fine granularity is costly 2 Solution: Mobile Traffic Super-Resolution (MTSR) 3 Improve the granularity of traffic measurements by up to 100× ZipNet + GAN Outperform other interpolation approaches Work well with anomaly traffic Chaoyun Zhang et al ZipNet-GAN December 14, 2017 Chaoyun Zhang et al ZipNet-GAN December 01, 2017 Chaoyun Zhang et al ZipNet-GAN November 16, 2017 Chaoyun Zhang et al ZipNet-GAN November 30, 2017

56 Summary Summary Mobile traffic analysis requires fine-grained knowledge 1 Measuring mobile traffic with fine granularity is costly 2 Solution: Mobile Traffic Super-Resolution (MTSR) 3 Improve the granularity of traffic measurements by up to 100× ZipNet + GAN Outperform other interpolation approaches Work well with anomaly traffic Chaoyun Zhang et al ZipNet-GAN December 14, 2017 Chaoyun Zhang et al ZipNet-GAN December 01, 2017 Chaoyun Zhang et al ZipNet-GAN November 16, 2017 Chaoyun Zhang et al ZipNet-GAN November 30, 2017

57 Summary Summary Mobile traffic analysis requires fine-grained knowledge 1 Measuring mobile traffic with fine granularity is costly 2 Solution: Mobile Traffic Super-Resolution (MTSR) 3 Improve the granularity of traffic measurements by up to 100× ZipNet + GAN Outperform other interpolation approaches Work well under anomalous traffic situations Chaoyun Zhang et al ZipNet-GAN December 14, 2017 Chaoyun Zhang et al ZipNet-GAN November 16, 2017 Chaoyun Zhang et al ZipNet-GAN December 01, 2017 Chaoyun Zhang et al ZipNet-GAN November 30, 2017

58 Questions? Questions? Summary chaoyun.zhang@ed.ac.uk
Chaoyun Zhang et al ZipNet-GAN December 14, 2017 Chaoyun Zhang et al ZipNet-GAN December 01, 2017 Chaoyun Zhang et al ZipNet-GAN November 16, 2017 Chaoyun Zhang et al ZipNet-GAN November 30, 2017

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