There were two options for the course project. Students either chose their own topic ("Final Project") or built models for reading comprehension on the SQuAD dataset ("Default Final Project").

Prize Winners

Congratulations to our prize winners for having exceptional class projects!

Final Project Prize Winners

1. Beating Atari with Natural Language Guided Reinforcement Learning by Alexander Antonio Sosa / Christopher Peterson Sauer / Russell James Kaplan
2. Image-Question-Linguistic Co-Attention for Visual Question Answering by Shutong Zhang / Chenyue Meng / Yixin Wang
3. Ruminating Neural Networks with Auto-regressive Attention Units by Jin Xie / Hao Sheng / Junzi Zhang

Outstanding posters

• Sequence to Sequence Model for Video Captioning by Yu Guo / Yue Liu / Bowen Yao
• Grounded Learning of Color Semantics with Autoencoders by Dev Bhargava / Gabriel Michael Vega / Blue Belmont Sheffer
• Power to the People: Using Deep Learning to Predict Power Relations by Angela Kong / Catherina Xu / Michelle Sau-Ming Lam
• CALYPSO: A Neural Network Model for Natural Language Inference by Colin Man / Kat Elizabeth Gregory / Kenny Xu
• DeepZip: Lossless Compression using Recurrent Networks by Kedar Tatwawadi

Default Final Project Prize Winners

1. Reading Comprehension on the SQuAD Dataset by Fnu Budianto
2. Question Answering System with Bi-Directional Attention Flow by Fei Xia / Junjie Ke / Yolanda Wang

Outstanding posters

• Finding Answers with Convolution Attention Stacks by Yair Carmon
• Reading Comprehension by Joe Wang
• Coattention-Based Neural Network for Question Answering by Cristian Zanoci / Jim Michael Andress
• Natural Language Question-Answering using Deep Learning by Fengjiao Lyu / Rajarshi Roy / Bowen Liu
• Iterative Attention Network for Question Answering by Tom Charles Henighan

Sponser Prize

• Modeling the Dynamic Framing of Controversial Topics in Online Communities by Julia Elizabeth Mendelsohn

Audience Selection Prize

• Beating Atari with Natural Language Guided Reinforcement Learning by Alexander Antonio Sosa / Christopher Peterson Sauer / Russell James Kaplan

Final Projects

Project Name	Authors
Deep Almond: A Deep Learning-based Virtual Assistant	Rakesh Ramesh / Giovanni Campagna
Effective Word Representation for Named Entity Recognition	Wendi Liu / Eric Li / Tim Hsieh
Learning Effective Embeddings from Medical Notes	Sebastien Pierre Romain Dubois / Nathanael Romano
An Examination of the CNN/DailyMail Neural Summarization Task	Eduardo Torres Montano / Liezl Legaspi Puzon / Vincent Chen
Word Sense Disambiguation Using Skip-Gram and LSTM Models	Armin Justin Namavari / Tyler Otha Smith / Shrey Gupta
Sequential LSTM-based Encoder for NLI	Ankita Sharma / Yokila Arora
Looking for Low-proficiency Sentences in ELL Writing	Shayne Miel
Natural Language Inference with Attentive Neural Networks	Julien Juilliard Kawawa-Beaudan / Varun Kumar Vijay / Kenny Kin Fai Leung
Neural Image Captioning for Intelligent Vehicle-to-Passenger Communication	Fredrik Karl Anders Gustafsson
Neural Stance Detectors for Fake News Challenge	Shanshan Xu / Quan Zhou / Qi Zeng
Automated Essay Feedback	Sawyer Birnbaum / Noah Samuel Arthurs
Discourse Parsing via Weighted Bag-of-Words, Coattention Neural Encoder, and Coattentative Convolutional Neural Network	Alex Fu / Yang Yuan / Borui Wang
Speech recognition with DNN-LAS	Jack Jin / Pengda Liu / Geng Zhao
TrumpBot: Seq2Seq with Pointer Sentinel Model	Filip Zivkovic
Implementing A Neural Cache LSTM	Christina Wadsworth / Raphael Martin Palefsky-Smith
Natural Language Learning Supports Reinforcement Learning	Andrew Kyle Lampinen
From Vision to NLP: A Merge	Alisha Mangesh Rege / Payal Bajaj
Learning to Rank with Attentive Media Attributes	Yang Yang / Baldo Antonio Faieta
Summarizing Git Commits and GitHub Pull Requests Using Sequence to Sequence Neural Attention Models	Ali-Kazim Zaidi
Neural Networks in Predicting Myers Brigg Personality Type From Writing Style	Anthony Kai Kwang Ma / Gus Liu
Estimating High-Dimensional Temporal Distributions Application to Music & Language Generation	Adrien Descamps / Maxime Alexandre Voisin
“Is it true?” – Deep Learning for Stance Detection in News	Shruti Bhargava / Neel Vinod Rakholia
Abstract Meta-Concept Features for Text-Illustration	Ines Chami
Detecting Key Needs in Crisis	Emma Marriott / Emma Marriott / Tulsee Doshi / Jay H Patel
Towards Automatic Identification of Fake News: Headline-Article Stance Detection with LSTM Attention Models	John Merriman Sholar / Saachi Jain / Sahil Chopra
Image Titles - Variations on Show, Attend and Tell	Robert Konrad / Vincent Sitzmann / Timon Dominik Ruban
Fake News, Real Consequences: Recruiting Neural Networks for the Fight Against Fake News	Chris Coffey Proctor / Richard Lee Davis
Image Captioning with Pragmatics	Noam Weinberger / Nico Manuel Chaves / Reuben Harry Cohn-Gordon
What’s good for the goose is good for the GANder - Comparing Generative Adversarial Networks for NLP	Brendan Mooney Corcoran / Christina Jenny Hung
Implementation and Optimization of Differentiable Neural Computers	Carol Hsin
Cosine Siamese Models for Stance Detection	Delenn Tzu Chin / Kevin Chen / Akshay Kumar Agrawal
A Neural Chatbot with Personality	David Rey Morales / Huyen Thi Khanh Nguyen / Tessera Chin
Deep Classification and Generation of Reddit Post Titles	Rolland Wu He / Tyler Foster Chase / Will Qiu
Comment Abuse Classification with Deep Learning	Theodora Chu / Max Wang / Kylie Amanda Jue
Writing Style Conversion using Neural Machine Translation	Se Won Jang / Jesse Min / Mark Kwon
Abstractive Text Summarization using Attentive Sequence-to-Sequence RNNs	Abiel Gutierrez / Elliott Morgan Jobson
Neural Conversational Model with Mutual Information Ranking	Chenye Zhu / Harrison Chi-Wei Ho
Exploring the Effects of External Semantic Data on Word Embeddings	William Chun Ki Hang / Brian Hu Zhang / Zihua Liu
Music Composition using Recurrent Neural Networks	Axel Sly / Yuki Inoue / Nipun Agarwala
Detecting and Identifying Bias-Heavy Sentences in News Articles	Shreya Shankar / Nick Paul Hirning / Andy Shiangjuei Chen
Neural Joke Generation	He Ren / Quan Yang
Named Entity Recognition and Compositional Morphology for Word Representations in Chinese	Christopher Heung / Emily Ling / Cindy Shinying Lin
Tagging Patient Notes With ICD-9 Codes	Sandeep Ayyar / Oliver John Bear Don't Walk
GraphNet: Recommendation System Based on Language and Network Structure	Xin Li / Rex Ying / Yuanfang Li
“Unmatched” Attention for Natural Language Inference	Homero Gabriel Roman Roman / Vinson Luo / Alex Tamkin
Aiding Sentiment Evaluation with Social Network	Fan Yang / Pengfei Gao / Hao Yin
Reversing Dictionaries and Solving Crossword Clues with Deep Learning	Meena Chetty / Viraj R Mehta
Quora Question Duplication	Elkhan Dadashov / Sukolsak Sakshuwong / Katherine Yu
Automatic Code Completion	Lindsey Makana Kostas / Tara Gayatri Balakrishnan / Adam Palazzo Ginzberg
Deep Causal Inference for Average Treatment Effect Estimation of Poems Popularity	Derek Farren
Distributed representations of politicians	Bobbie Macdonald
Predicting Stock Movement through Executive Tweets	Mike Logan Jermann
Information Retrieval from Surgical Reports using Data Programming	Zeshan Mohammed Hussain / Hardie Hardie Cate / Elliott Jake Chartock
Stance Detection for the Fake News Challenge: Identifying Textual Relationships with Deep Neural Nets	Philipp Thun-Hohenstein / Ali Khalid Chaudhry / Darren Baker
Predicting Short Story Endings	Michael Mernagh
Comparing Deep Learning and Conventional Machine Learning for Authorship Attribution and Text Generation	Francisco Alejandro Romero / Gregory Charles Luppescu
Duplicate Question Pair Detection with Deep Learning	Travis Addair
Song Title Prediction with Bidirectional Recurrent Sequence Tagging	Ryan Holmdahl
Music Genre Classification by Lyrics using a Hierarchical Attention Network	Alex Tsaptsinos
Recurrent and Contextual Models for Visual Question Answering	Abhijit Sharang / Eric Chun Kai Lau
Identifying Nominals with No Head Match Co-references Using Deep Learning	Matthew David Stone / Ramnik Arora
Stance Detection for Fake News Identification	Atli Kosson / Eli Wang / Damian Mrowca
Transfer Learning on Stack Exchange Tags	Shifan Mao / Weiqiang Zhu / Jake Dong
Detecting Duplicate Questions with Deep Learning	Stuart Lee Sy / Christopher Tzong-Ran Yeh / Yushi Homma
Ensembling Insights for Baseline Text Models	Henry Richman Ehrenberg / Dan Iter
Deep Poetry: Word-Level and Character-Level Language Models for Shakespearean Sonnet Generation	Stanley Xie / Max Austin Chang / Ruchir Rastogi
Abstractive Summarization with Global Importance Scores	Vivian Hoang-Dung Nguyen / Shivaal Kaul Roy
Too Many Questions	Jeffrey Jialei Zhang / Ann He
Awkwardly: A Response Suggester	Kai-Chieh Huang / Quinlan Rachel Jung
Evaluating Generative Models for Text Generation	Raunaq Rewari / Prasad Kawthekar / Suvrat Bhooshan
Using Neural Networks to Predict Emoji Usage from Twitter Data	Connie Xiao Zeng / Luda Zhao
The Challenge of Fake News: Automated Stance Detection via NLP	Jeff T. Sheng / Evan Taylor Ragosa Rosenman
RNNs for Stance Detection between News Articles	Graham John Yennie / Jason Yu Chen / Joe Robert Johnson
“The Pope Has a New Baby!” Fake News Detection Using Deep Learning	Samir Bajaj
Transfer Learning: From a Translation Model to a Dense Sentence Representation with Application to Paraphrase Detection	Max Ferguson
Stance Detection for the Fake News Challenge with Attention and Conditional Encoding	Ferdinand Legros / Oskar Jonathan Triebe / Stephen Robert Pfohl
Language Dynamics analysis through Word2Vec Embeddings	Jeha Yang / Claire Louise Donnat
TL;DR: Improving Abstractive Summarization Using LSTMs	Sang Goo Kang / Samuel Kim
News Article Summarization with Attention-based Deep Recurrent Neural Networks	Chao Wang / Chang Yue / Yoyo Yu
Biomedical Named Entity Recognition Using Neural Networks	George Mavromatis
Lazy Prices: Vector Representations of Financial Disclosures and Market Outperformance	Alex Hanyu Lin / Victor Cheung / Kai Maroon Kuspa
Coreferent Mention Detection using Deep Learning	Aditya Barua / Piyush Sharma
Hybrid Word-Character Neural Machine Translation for Modern Standard Arabic	Siggi Kjartansson / Pamela Toman
Autoregressive Attention for Parallel Sequence Modeling	Jeremy Andrew Irvin / Dillon Anthony Laird
The ROUGE-AR: A Proposed Extension to the ROUGE Evaluation Metric for Abstractive Text Summarization	Sydney Chase Maples
Understanding and Predicting the Usefulness of Yelp Reviews	David Zhan Liu
Are Latent Sentence Vectors Cross-Linguistically Invariant?	Michael Hermann Hahn
Neural Review Ranking Models for Ads at Yelp	Florian Karl Hartl / Vishnu Purushothaman Sreenivasan
Melody-to-Chord using paired model and multi-task learning language modeling	Yen-Kai Huang / Wei-Ting Hsu / Mu-Heng Yang
Classifying Reddit comments by subreddit	Ian Tam
Dating Text From Google NGrams	Aashna Shroff / Kelsey Marie Josund / Akshay Rampuria
Universal Dependency Parser: A Single Parser for Many Languages on Arc-Swift	Frank Fan / Michelle Guo
Exploring Optimizations to Paragraph Vectors	Zoe Michelle Robert / Maya Thadaney Israni / Gabbi Samantha Fisher
Determining Entailment of Questions in the Quora Dataset	Albert Jia-Xiang Tung / Eric Yanmin Xu
Extending the Scope of Co-occurrence Embedding	Jack Mi / Yuetong Wang / Jiren Zhu
Smart Initialization Yields Better Convergence Properties in Deep Abstractive Summarization	Maneesh Dilip Apte / Casey Chu / Liam O'hart Kinney
LSTM Encoder-Decoder Architecture with Attention Mechanism for Machine Comprehension	Brian Magid Higgins / Eugene Jinyoung Nho
Deep Learning based Authorship Identification	Chen Qian / Tianchang He / Rao Zhang
Computational models for text summarization	Leo Michael Keselman / Ludwig Schubert
Multitask Learning and Extensions of Dynamic Coattention Network	Keven Wang / Xinyuan Huang
Predicting State-Level Agricultural Sentiment with Tweets from Farming Communities	Darren Hau / Swetava Ganguli / Jared Alexander Dunnmon / Brooke Elena Husic
“Nowcasting” County Unemployment Using Twitter Data	Thao Thi Thach Nguyen / Megha Bhushan Srivastava
Rationalizing Sentiment Analysis in Tensorflow	Henry John Neeb / Kevin Eugene Shaw / Aly Rachel Kane
Word2Vec using Character n-grams	Varsha Sankar / Radhika Pramod Patil / Deepti Sanjay Mahajan
Natural Language Inference for Quora Dataset	Kyu Koh Yoo / Muhammad Majid Almajid / Yang Wong
Logfile Failure Prediction using Recurrent and QuasiRecurrent Neural Networks	Isuru Umayangana Daulagala / Austin Jiao
Abstractive Text Summarization with Quasi-Recurrent Neural Networks	Jeffrey Kenichiro Hara / Sho Arora / Peter August Adelson
Tell Me What I See	Victor Valeriiovych Makoviichuk / Peter Lapko / Boris Borisovich Kovalenko
Backprop to the Future: A Neural Network Approach to Linguistic Change over Time	Dai Shen / Michael Xing / Eun Seo Jo

Default Final Projects

Project Name	Authors
Natural Language Processing with Deep Learning Reading Comprehension	Wissam Baalbaki / Dan Zylberglejd
Reading Comprehension	Vishakh Hegde
Reading Comprehension on SQuAD Dataset	Andrew Nicholas Declerck / Kevin Thomas Rakestraw
Dynamic Coattention with Sentence Information	Alex Heneghan Ruch
Reading Comprehension On SQuAD Using Tensorflow	Micah Daniel Silberstein / Chase Brandon / Michael Holloway
#SQuADGoals: A Comparative Analysis of Models for Closed Domain Question Answering	Eric Mutua Musyoka / Andrew Elijah Duffy / Dan Michael Shiferaw
Reading Comprehension with Coattention Encoders	Chan Lee / Jae Hyun Kim
Neural Question Answer Systems: Biased Perspectives and Joint Answer Predictions.	Nick Paul Troccoli / Lucy L. Wang / Sam Redmond
An exploration of Approaches for the Stanford Question Answering Dataset	Charles Chen
Question Answering on the SQuAD Dataset	Moosa Hasan Zaidi / Nawaf Adel Alnaji
Question Answering	Jacob Elias Perricone / Blake Jennings
Question Answering on the SQuAD Dataset	Dangna Li
Neural tetworks for text-based answer extraction	Brian Russell Hicks
Dynamic Coattention Networks for Reading Comprehension	Hayk Tepanyan
Bifocal Perspectives for Machine Comprehension	Andrew Shao-Chong Lim / Adam Muhannad Abdulhamid / Pavitra Tirumanjanam Rengarajan
Building upon Multi-Perspective Matching for SQuAD	Louis Yvan Duperier / Yoann Le Calonnec
Recurrent Neural Networks and Machine Reading Comprehension	Hana Lee
Match LSTM based Question Answering	Hershed Tilak / Yangyang Yu / Michael Cannon Lowney
Exploration and Analysis of Three Neural Network Models for Question Answering	William Jiang
Question Answering on the SQuAD Dataset	Mudit Jain
Question Answering	Peeyush Agarwal
Harder Learning: Improving on Dynamic Co-Attention Networks for Question-Answering with Bayesian Approximations	Marcus Vincent Gomez / Brandon Bicheng Cui / Udai Baisiwala
Extractive Question Answering Using Match-LSTM and Answer Pointer	Jake Alexander Rachleff / Cameron John Van De Graaf / Alexander Haigh
SQuAD Question Answering Problem: A match-lstm implementation	Philippe Fraisse
Implementation and Improvement of Match-LSTM in Question-Answering System	Ben Zhang / Haomin Peng
Coattention-Based Multi-Perspective Matching Network for Machine Comprehension	Qiujiang Jin / Bowei Ma
Deep Question Answering using Bi-directional Attention-based LSTMs and Weighted Distribution Penalization	Akhil Prakash / Pranav Ananth Sriram / Vineet Ahluwalia
Deep Learning for Question Answering on the SQUAD	Reza Takapoui / Ramtin Keramati / Kian Kevin Katanforoosh
SQuAD Reading Comprehension with Attention	Austin Hou
An LSTM Attention-based Network for Reading Comprehension	Rafa Goissis Setra
Question Answering on the SQuAD Dataset	Brad Garrison Girardeau
Question Answering on SQuAD	Haque Muhammad Ishfaq / Chenjie Yang
Question Answering with Deep Learning	Tristan Drake Mcrae
Understanding Multi-Perspective Context Matching for Machine Comprehension	Cindy Catherine Orozco Bohorquez
Machine Comprehension Using Multi-Perspective Context Matching and Co-Attention	Tarun Gupta / Andrei Bajenov
Question Answering Using Bi-Directional RNN	Aojia Zhao / Simon Kim
Reading Comprehension with SQuAD	Archa Jain
Reading Comprehension	Clare Chen / Kevin Rui Luo
Exploring Different Matching/Attention Mechanism for Machine Comprehension Task on SQuAD Dataset	George Pakapol Supaniratisai / Nattapoom Asavareongchai
Implementation of Multi-Perspective Context Matching for Machine Comprehension	Wen Yau Aaron Loh
Question Answering with SQuAD: Variations on Multi-Perspective Context Matching	Jason Freeman / Raine Morgan Hoover
Reading Comprehension	Jason Liu / Christina Kao / Christopher Vo
A Convolution Network Approach to Machine Comprehension	Lisa Yan
Deep Coattention Networks for Reading Comprehension	Amy Lawson Bearman
Reading Comprehension	Ryan Patrick Burke / Leah Lynn Brickson / Alexandre Robicquet
Machine Comprehension using Dynamic Recurrent Neural Network and Gated Recurrent Unit	Yi-Hong Kuo / Hsin-Ya Lou / Hsiang-Yu Yang
Neural Network-based Question Answering System	Sriraman Madhavan / Sanyam Mehra / Kushaagra Goyal
Rolling Deep with the SQuAD: Question Answering	Tanuj Thapliyal / Dhruv Amin / Reid Westwood
Question Answering with Multi-Perspective Context Matching	Joey William Blackshaw Asperger
Exploration of Attention in Question Answering	Anthony Perez
Machine Comprehension with Exploration on Attention Mechanism	Chen Guo
Machine Comprehension with Modified Bi-Directional Attention Flow Network	Mingxiang Chen / Sijun He / Jiajun Sun
Reading Comprehension	Joris Van Mens / Nickolas Samuel Westman / Ilya Kuleshov
Random Coattention Forest for Question Answering	Yi-Chun Chen / Ting-Po Lee / Jheng-Hao Chen
Decoding Coattention Encodings for Question Answering	Qandeel Tariq / John Wang Clow / Alex Kolchinski
Multi-Perspective Context Matching for SQuAD Dataset	Huizi Mao / Xingyu Liu
Improving Match-LSTM for Machine Comprehension	Mike Yu / Kevin Foschini Moody / Dennis Xu
SQuAD Reading Comprehension Learning	Thomas Pascal Jean Ayoul / Sebastien Nathan Raphael Levy
Exploring Deep Learning Models for Machine Comprehension on SQuAD	Joseph Kuruvilla Charalel / Yifei Feng / Junjie Zhu
Reading Comprehension	Suraj Heereguppe Radhakrishna / Chiraag Sumanth / Jayanth Ramesh
Simple Dynamic Coattention Networks	Wenqi Wu
Question Answering Using Regularized Match-LSTM and Answer Pointer	Debnil Arindam Sur / Ellen Lindsey Blaine
Extending Match-LSTM	Keegan Rochard Mosley / Sebastian Goodman
Global Span Representation Model for Machine Comprehension on SQuAD	Sunmi Lee / Jaebum Lee
BiDAF Model for Question Answering	Genki Kondo / Ramon Tuason / Daniel Grazian
A new model for Machine Comprehension via multi-perspective context matching and bidirectional attention flow	Nima Hamidi / Amirata Ghorbani
Co-Attention with Answer-Pointer for SQuAD Reading Comprehension Task	Mindy Lea Yang / Tommy Fan / Chenyao Yu
Reading Comprehension on SQuAD	Meghana Vijay Rao / Brexton Pham / Zachary Davis Taylor
Coattention Answer-Pointer Networks for Question Answering	Yanshu Hong / Tian Zhao / Yiju Hou
Coattention Model for Question Answering	Marie Eve Vachovsky / Tina Ivy Vachovsky
Modular Sequence Attention Mix Model	Ahmed Hussain Jaffery / Kostya Sebov
Question Answering Using Match-LSTM and Answer Pointer	Brandon Chauloon Yang / Cindy Wang / Annie Hu
SQuAD Question Answering using Multi-Perspective Matching	Shloka Mitesh Desai / Sheema Usmani / Zach Daniel Maurer
Relevancy-Scaled Deep Co-Attentive Networks for Question Answering	Varun Abhijit Gupta / Orry Chris Despo / Nadav Aharon Hollander
A simple sequence attention model for machine comprehension	Marcello Mendes Hasegawa
Question Answering with Recurrent Span Representations	Timothy Man Hay Lee / Kevin Xinzhi Wu / John Louie
Question Answering on the SQuAD Dataset with Part-of-Speech Tagging	Nancy Xu / Philip Ken-Ka Hwang / Joan Creus-Costa
NQSotA Continuation Curriculum Learning with Question Answering on the SQuAD Dataset	Rahul Sunil Palamuttam / Luke Taylor Johnston / William Chen
CS 224N Assignment 4: Question Answering on SQuAD	Kevin Matthew Garbe / Aykan Ozturk / Huseyin Atahan Inan
Seq2seq-Attention Question Answering Model	Wenqi Hou / Yun Nie
Question Answering on the SQuAD Dataset Using Multi-Perspective Context Matching	Sam Edward Herbert Colbran / Stanislav Fort
Bidirectional Attention Flow Model for Reading Comprehension	Michael Painter / Bardia Beigi / Soroosh Hemmati
Maching Comprehension using SQuAD and Deep Learning	Josh Robert King / Filippo Ranalli / Ajay Uday Mandlekar
Machine Comprehension with MMLSTM and Clustering	Frank Anthony Cipollone / Zachary Barnes / Tyler Romero
Dynamic Coattention Networks with Encoding Maxout	Morgan Lee Tenney / Thaminda Mewan Edirisooriya / Hansohl Eliott Kim
Implementation and New Variants Exploration of the Multi-Perspective Context Matching Deep Neural Network Model for Machine Comprehension	Yutong Li / Prateek Murgai
Attention-based Recurrent Neural Networks for Question Answering	Dapeng Hong / Billy Wan
Co-Dependent Attention on SQuAD	Siyue Wu / Fabian Chan / Xueyuan Mei
Start and End Interactions in Bidirectional Attention Flow for Reading Comprehension	Sean Thomas Rafferty / Ted Harbin Li
Implementing Multi-Perspective Context Matching for the SQuAD Task in TensorFlow	Christopher Michael Pesto
CAESAR: Context-Awareness Enabled and Summary-Attentive Reader	Kshitiz Tripathi / Long-Huei Chen / Mario Sergio Rodriguez
Ensemble Learning For Machine Comprehension: Bidirectional Attention Flow Models	Divya Shree Saini / Stephen Ou / William Adams Du
An End-to-End Neural Architecture for Reading Comprehension	Ned Joseph Danyliw / Miguel Sebastian Camacho-Horvitz / Meredith Noelani Burkle
Neural Methods for Question Answering	Ayush Kanodia / Manik Dhar / Pratyaksh Sharma
Implementation and Analysis of Match-LSTM for SQuAD	Michael Graczyk
Multiple Turn Comprehension for the BiDirectional Attention Flow Model	Thomas Liu
Question Answering on the SQuAD Dataset	Do-Hyoung Park / Vihan Sankaran Lakshman
Answering SQuAD	Faraz Waseem / Atishay Jain
Game, Set, Match-LSTM: Question Answering on SQuAD	Eric Osemen Ehizokhale / Ian Narciso Torres
Bidirectional LSTM-RNN with Bi-Attention for reading comprehension	Guoxi Xu / Bera Shi / Ziyi Yang
Filter-Context Dynamic Coattention Networks for Question Answering	Yangxin Zhong / Jian Huang / Peng Yuan
Question Answering System using Dynamic Coattention Networks	Adeline Emily Wong / Bojiong Ni / James Shi
Machine Question and Answering	Diana Dan Khanh Le / Malina Jiang / Joseph Chang
Question Answering on the SQuAD Dataset	Saghar Hosseinisianaki / Yun Yun Li
Learning Reading Comprehension with Neural Nets	Jason Huang / Li Cai / Charles Huyi
Convolutional Encoding in Bidirectional Attention Flow for Question Answering	Daniel Roy Miller
Incorporating Part-of-Speech tags and Named Entities into Match-LSTM	Raunak Kasera / Dilsher Ahmed
Reading Comprehension with Deep Learning	Atticus Reed Geiger / Dylan Ziqing Liu
Unilateral Multi-Perspective Matching for Machine Comprehension	Max Calvin Schorer / Jason Wang / Sigberto Viesca
Question Answering on the SQuAD Dataset	Xin Jin / Milind Mukesh Rao / Abbas Kazerouni
Reading Comprehension on the Stanford Question Answering Dataset	Shashwat Udit
Machine Comprehension for SQuAD dataset	Vikas R Bahirwani / Erika Debra Menezes
Machine Comprehension with Deep Learning on SQuAD dataset	Neha Gupta / Yianni Dimitrios Laloudakis / Yash Vyas