1 INTRODUCTION

2 A VERY BRIEF HISTORICAL OVERVIEW - OR WHAT WE ARE NOT COVERING IN THIS REVIEW

3 DEEP LEARNING FOR COMPUTER VISION TASKS IN ASTRONOMY

3.1 Classification

3.2 Segmentation, deblending and pixel-level classification

3.3 Improving data quality

3.4 Emulating astronomical images

4 DEEP LEARNING FOR INFERRING PHYSICAL PROPERTIES OF GALAXIES

4.1 Neural Networks as fast emulators

4.2 Galaxy physical properties from simulations

5 DEEP LEARNING FOR DISCOVERY

5.1 Visualization of large datasets

5.2 Outlier detection

5.3 Discovery of Physical Laws

6 DEEP LEARNING FOR COSMOLOGY

6.1 Accelerating simulations

6.2 Deep learning for cosmological inference

7 FINAL THOUGHTS: ASSESSING THE PRESENT AND FUTURE OF DEEP LEARNING FOR GALAXY SURVEYS

7.1 On the penetration of deep learning techniques in astronomy

7.2 Measuring the impact of deep learning

7.3 Challenges

8 SUMMARY