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List of Papers

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Paper presentation

Date Name Paper number Title Link to the paper Link to the summary
Oct 12 (example) Ri Wang Sequence to sequence learning with neural networks. Paper Summary
Oct 24 Sakif Khan 1 Improved Variational Inference with Inverse Autoregressive Flow [1] [2]
Oct 24 2
Oct 24 3
Oct 26 4
Oct 26 5
Oct 26 6
Oct 31
Oct 31
Oct 31
Nov 2
Nov 2
Nov 2
Nov 7 Dishant Mittal meProp: Sparsified Back Propagation for Accelerated Deep Learning with Reduced Overfitting Paper
Nov 7
Nov 7 Rahul Iyer
Nov 9 ShuoShuo Liu Learning the Number of Neurons in Deep Networks Paper
Nov 9 Aravind Balakrishnan FeUdal Networks for Hierarchical Reinforcement Learning [3]
Nov 9 Varshanth R Rao Cognitive Psychology for Deep Neural Networks: A Shape Bias Case Study Paper
Nov 14 Avinash Prasad Coupled GAN
Nov 14 Nafseer Kadiyaravida Dialog-based Language Learning Paper Summary
Nov 14
Nov 16 Hamidreza Shahidi Teaching Machines to Describe Images via Natural Language Feedback
Nov 16 Sachin vernekar Natural-Parameter Networks: A Class of Probabilistic Neural Networks Paper Summary
Nov 16 Yunqing HE LightRNN: Memory and Computation-Efficient Recurrent Neural Networks [4]
Nov 21 Aman Jhunjhunwala Curiosity-driven Exploration by Self-supervised Prediction Paper Summary
Nov 21 Peiying Li Deep Learning without Poor Local Minima [5] Summary
Nov 21 Ashish Gaurav Deep Exploration via Bootstrapped DQN Paper Summary
Nov 23 Venkateshwaran Balasubramanian
Nov 23 Ershad Banijamali Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks Paper
Nov 23 Dylan Spicker Unsupervised Domain Adaptation with Residual Transfer Networks Paper
Nov 28 Mike Rudd 1 Deep Transfer Learning with Joint Adaptation Networks Paper Summary
Nov 28
Nov 28
Nov 30
Nov 30
Nov 30