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Sep 25, 2020 neurosymbolic coursework
Logical Neural Network

Ryan Riegel, et al. (arxiv 2020) proposes to build Neural Network by adding one neuron for each logical gate and literal in a logic formulae and hence building a neural framework for logical inference. This article reviews their work. It was written jointly with Siwen Yan, as part of the course on NeuroSymbolic systems by Prof. Sriraam Natarajan.
Sep 22, 2020 neurosymbolic coursework
Augmenting Neural Networks with First-order Logic

Declarative knowledge, first-order rules are used in ILP (a lot) to reduce dependency on the data. Since deep neural network are data hungry, can we use some first-order rules and reduce their data requirement? This post reviews the work by Tao and Srikumar (ACL 2019) which attempts to answer this research question.
Apr 29, 2020 GNN adversary coursework
Attacking GNN with Meta Learning

This article reviews a very exciting ICLR 2019 paper: Adversarial Attacks on Graph Neural Networks via Meta Learning. This was originally written as part of a class assignment at UT dallas.
Apr 4, 2020 few-shot GNN coursework
Few-Shot Learning with GNN

My notes on Victor Garcia, Joan Bruna, ICLR 2018. Written as part of the Complex Networks course by Prof. Feng Chen.
Mar 27, 2020 metalearning coursework
Model-Agnostic Meta-Learning

My notes on Chelsea Finn, Pieter Abbeel, Sergey Levine, ICML 2017. Written as part of the Complex Networks course by Prof. Feng Chen.
Feb 26, 2020 GNN coursework
Understanding Attention and Generalization in Graph Neural Networks

My notes on Boris Knyazev, Graham W. Taylor, and Mohamed R. Amer, NeurIPS 2019. Written as part of the Complex Networks course by Prof. Feng Chen.
Feb 17, 2020 GNN coursework
Graph Attention Networks

My notes on Peter Veličković et al. ICLR 2018. Written as part of the Complex Networks course by Prof. Feng Chen.
Feb 5, 2020 GNN coursework
Graph Convolutional Networks

My notes on Thomas N Kipf and Max Welling ICLR 2017. Written as part of the Complex Networks course by Prof. Feng Chen.
Oct 28, 2019 RL hierarchy coursework
Hierarchical Reinforcement Learning

An overview of Hierarchical RL. Written as part of Advanced RL course by Prof. Sriraam Natarajan.
Nov 4, 2018 advice coursework survey
Advice based relational learning

As part of an independent study with Prof. Sriraam Natarajan, I read advice-based methods for data in relational first-order logic. Here are my notes on it.
Jan 31, 2018 SRL coursework
BLOG: Relational Modeling with Unknown Objects

BLOG by Milch et al. provides a language which help us model random functions and probabilistic properties of unknown objects. Going beyong Herbrand Universe. This mainly reviews the key contributions and limitations of that paper. Written as part of the Statistical Relational Learning course by Prof.Sriraam Natarajan.