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readme.md

readme.md

Optimization / Training Techniques

Id Schedule Presenters Paper(s) Link(s)
1. 7th April (1) Uday Shankar Shanthamallu and Xin Ye Batch normalization: Accelerating deep network training by reducing internal covariate shift (2015), S. Loffe and C. Szegedy [pdf]
Batch Renormalization: Towards Reducing Minibatch Dependence in Batch-Normalized Models, S. Ioffe. [pdf]
2. 24th March (4) Anil Motupalli and Trideep Rath Adam: A method for stochastic optimization (2014), D. Kingma and J. Ba [pdf]
3. 28th April (1) Garret Decker and Manali Diwakar Trivedi(2) and Praveen ShivaPrasad(5) Layer Normalization (2016), J. Ba et al. [pdf]
4. 21st April (2) Laxmikant Patil(7) and Anurag Solanki(9) and Ashkan Aleali Learning to learn by gradient descent by gradient descent (2016), M. Andrychowicz et al. [pdf]
5. 24th March (3) Avinash Reddy Kaitha and Amin Salehi Understanding deep learning requires rethinking generalization, (2017) C. Zhang et al. [pdf]
6. 31st March (4) Arun Karthikeyan and Chandrakanth Reddy Mamillapalli Overcoming catastrophic forgetting in neural networks (2017) J Kirkpatrick et. al, [pdf]
An Empirical Investigation of Catastrophic Forgetting in Gradient-Based Neural Networks (2015) I. Goodfellow et. al, [pdf]

Unsupervised / Generative Models

Id Schedule Presenter Paper(s) Link(s)
7. 31st March (1) Perikumar Mukundbhai Javia and Aarav Madan Generative adversarial nets (2014), I. Goodfellow et al. [pdf]
8. 7th April (2) Vatsal Mahajan and Nishi Shah and Saurabh Singh Improved techniques for training GANs (2016), T. Salimans et al. [pdf]
Unsupervised representation learning with deep convolutional generative adversarial networks (2015), A. Radford et al. [pdf]
9. 14th April (2) Kshama Jain and Siddhant Prakash InfoGAN: Interpretable Representation Learning by Information Maximizing Generative Adversarial Nets (2016), Xi Chen et. al, [pdf]
Learning from Simulated and Unsupervised Images through Adversarial Training (2016) Shrivatsava et al., [pdf]
10. 21st April (3) Bijan Fakhri and Pradyumna Kadambi and Prajwal Paudyal Wasserstein GAN, M. Arjovsky et al. [pdf]
11. 31sr March (2) Trevor Barron and Gopal Rao Kolli and Abhishek Kumar Energy-based Generative Adversarial Network (2016) Zhao et. al, [pdf]
12. 24th March (1) Arindam Mitra and Buddha Puneeth Nandanoor Transforming Autoencoders (2012), G. Hinton et al., [pdf]

Network Architecture

Id Schedule Presenter Paper(s) Link(s)
13. 31st March (3) Wenbo Tian and Aman Verma Identity Mappings in Deep Residual Networks (2016), K. He et al. [pdf]
Deep residual learning for image recognition (2016), K. He et al. [pdf]
14. 7th April (3) Rajagopaalan Sethuraman and Kowshik Thopalli Deep networks with stochastic depth (2016), G. Huang et al., [pdf]
15. 14th April (4) Sangdi Lin and Meredith Moore and Yanzhe Xu Fully convolutional networks for semantic segmentation (2015), J. Long et al. [pdf]
16. 21st April (4) Chia-Yu Hsu and Jau-Yuan Shiao Spatial transformer network (2015), M. Jaderberg et al., [pdf]
17. 14th April (3) Aastha Khanna and Hari Kripa Omalur Chandran and Manan Shah Densely connected convolutional networks (2016), G. Huang et al. [pdf]
18. 28th April (2) Prakhar Khandelwal and Stephen Mcaleer and Rudra Steerable CNNs (2017) T.S. Cohen et.al, [pdf]
19. 28th April (3) Zige Huang and Ragini Sai Sri Lakshmi Sistla and Gaurav Srivastava Rethinking the inception architecture for computer vision (2016), C. Szegedy et al. [pdf]
Inception-v4, inception-resnet and the impact of residual connections on learning (2016), C. Szegedy et al. [pdf]
20. 28th April (4) Lei Guo and Shanshi Huang and Ruibo Liu Semantic image segmentation with deep convolutional nets and fully connected CRFs, L. Chen et al. [pdf]

Network compression

Id Schedule Presenter Paper(s) Link(s)
21. 24th March (2) Saman Biookaghazadeh and Jajati Routray and Vishal Srivastava Deep compression: Compressing deep neural networks with pruning, trained quantization and huffman coding (2015), S. Han et al. [pdf]
22. 7th April (4) Anchit Agarwal(13) Unifying distillation and priviliged information (2017) Lopez-paz et. al, [pdf]
23. 14th April (1) Jitesh Kamble and Vishal Ishwar Naik and Bahar Shahrokhian Ghahfarokhi Optimal Brain Damage (1989) Y. LeCun et. al, [pdf]
24. 21st April (1) Pak Lun Kevin Ding and Duo Lu On the Number of Linear Regions of Deep Neural Networks (2014) Montúfar, Guido et. al, [pdf]
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