Papers I Read Notes and Summaries

Learning to Count Objects in Natural Images for Visual Question Answering

Introduction

  • Most of the visual question-answering (VQA) models perform poorly on the task of counting objects in an... Continue reading

Neural Message Passing for Quantum Chemistry

Introduction

  • The paper presents a general message passing architecture called as Message Passing Neural Networks (MPNNs) that... Continue reading


Unsupervised Learning by Predicting Noise

Introduction

  • Convolutional Neural Networks are extremely good feature extractors in the sense that features extracted for one... Continue reading


The Lottery Ticket Hypothesis - Training Pruned Neural Networks

Introduction

  • Empirical evidence indicates that at training time, the neural networks need to be of significantly larger... Continue reading


Cyclical Learning Rates for Training Neural Networks

Introduction

  • Conventional wisdom says that when training neural networks, learning rate should monotonically decrease. This insight forms... Continue reading


Improving Information Extraction by Acquiring External Evidence with Reinforcement Learning

Introduction

  • Information Extraction - Given a query to be answered and an external search engine, information extraction... Continue reading


An Empirical Investigation of Catastrophic Forgetting in Gradient-Based Neural Networks

Introduction

  • Catastrophic Forgetting refers to the phenomenon where when a learning system is trained on two tasks... Continue reading


Learning an SAT Solver from Single-Bit Supervision

Introduction

  • The paper presents NeuroSAT, a message passing neural network that is trained to predict if a... Continue reading


Neural Relational Inference for Interacting Systems

Introduction

  • The paper presents Neural Relational Inference (NRI) model which can infer underlying interactions in a dynamical... Continue reading


Stylistic Transfer in Natural Language Generation Systems Using Recurrent Neural Networks

Introduction