Papers I Read Notes and Summaries

Emergence of Grounded Compositional Language in Multi-Agent Populations

Introduction

  • The paper provides a multi-agent learning environment and proposes a learning approach that facilitates the emergence... Continue reading


A Semantic Loss Function for Deep Learning with Symbolic Knowledge

Introduction

  • The paper proposes an approach for using symbolic knowledge in deep learning systems. These constraints are... Continue reading


Hierarchical Graph Representation Learning with Differentiable Pooling

Introduction

  • Most existing GNN (Graph Neural Network) methods are inherently flat and are unable to process the... Continue reading


Imagination-Augmented Agents for Deep Reinforcement Learning

  • The paper presents I2A (Imagination Augmented Agent) that combines the model-based and model-free approaches leading to data efficiency... Continue reading


Kronecker Recurrent Units

Introduction

  • Recurrent Neural Networks have two key issues:


Learning Independent Causal Mechanisms

Introduction

  • The paper presents a very interesting approach for learning independent (inverse) data transformation from a set... Continue reading


Memory-based Parameter Adaptation

Introduction

  • Standard Deep Learning networks are not suitable for continual learning setting as the change in the... Continue reading


Born Again Neural Networks

Introduction

  • The paper explores knowledge distillation (KD) from the perspective of transferring knowledge between 2 networks of... Continue reading


Net2Net-Accelerating Learning via Knowledge Transfer

Notes

  • The paper presents a simple yet effective approach for transferring knowledge from a trained neural network... Continue reading


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