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Weekly Reading Group at DSG

This repository hosts a list of research papers and topics that we discuss on every Saturday in the group. We believe that reading research papers not only strengthens our concepts, but also helps in understanding the intuition behind the development of a particular idea, and the complete thought process of the author.

A collection of concise write-ups on each paper, with something noteworthy is also maintained here.

2021

Date Topic Presenters Notes
20th August, 2021 YOLO: You Only Look Once Apoorva, Shreya Summary
15th August, 2021 Training and Analysing Deep Recurrent Neural Networks Shreshtha, Manas Summary
10th August 2021 Visualizing and Understanding Convolutional Networks Pranjal, Praneeth Summary
26th June, 2021 Very Deep Convolutional Networks for Large-Scale Image Recognition Apoorva, Subodh Summary

2020

Date Topic Presenters Notes
4th October, 2020 Composition-Based Multi-Relational Graph Convolutional Networks (CompGCN) Anirudh Summary
22nd August, 2020 Attention Is All You Need Ankit, Yash, Ankit Aharwal Summary, Code
15th August, 2020 SPECTER: Document-level Representation Learning using Citation-informed Transformers, Neural Arithmetic Logic Units Anirudh, Aaryan Summary (Specter) Summary (NALU)
8th August, 2020 iSeeBetter: Spatio-temporal video super-resolution using recurrent generative back-projection networks & Other SRs Rohan, Saswat Summary
1st August, 2020 Deep Residual Learning for Image Recognition Abhinav, Shashwat, Shashank Summary, Code
18th July, 2020 Long Short-Term Memory (LSTM) Aaryan, Shruti, Ishan Summary, Code
4th July,2020 Generative Adversarial Nets Sahil, Vivek, Akshit Summary, Code
27th June, 2020 Tutorial on Variational Autoencoders Prankush, Vipul Summary
20th June, 2020 Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift, LayerNorm, GroupNorm, InstanceNorm Aaryan, Ishan, Anirudh Summary, Code
15th June, 2020 What Uncertainties Do We Need in Bayesian Deep Learning for Computer Vision? Rohan, Yash, Ankit Summary
12th June, 2020 PyTorch: An Imperative Style, High-Performance Deep Learning Library & Automatic differentiation in PyTorch Anirudh, Saswat Part of PyTorch Code Review Discussions in DSG
6th June, 2020 Distilling the knowledge in a neural network Shashwat, Akshit Summary, Code Teacher network, Code Student network
30th May, 2020 Learning to learn by gradient descent by gradient descent Shruti, Vivek, Shashank Summary, Code
23rd May, 2020 Mixed Precision Training Aaryan, Ishan, Anirudh Summary, Code
16th May, 2020 Selfie: Self-supervised Pretraining for Image Embedding Ankit, Prankush Summary
9th May, 2020 Explaining and Harnessing Adversarial Examples Abhinav, Sahil, Vipul Summary, Code

2017

Date Topic Presenters Notes
29th April, 2017 Fractional Max-Pooling Ajay Unagar Summary
10th Feb, 2017 Imagenet Classification with Deep Convolutional Neural Networks Karan Desai Summary