dsgiitr/reading-group

Discussions on papers, frameworks, blogs and ideas every Saturday.

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