## Quantum Circuit Decomposition

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An introduction to quantum circuit decomposition, a technique in quantum computing. Master’s project.

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While I plan to import the posts presented here into this website directly, for now this is just a collection of links to various blog posts and other informal publications.

** Published:**

An introduction to quantum circuit decomposition, a technique in quantum computing. Master’s project.

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In this post, I attempt to provide a clear explanation of the intuition behind policy gradient algorithms.

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These are the first part of my notes for chapter 3 of the Deep Learning book. They can also serve as a quick intro to probability.

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In this post I reproduce two papers in the field of metalearning: MAML and the similar Reptile.

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In this post, I reproduce the recent Uber paper “Deep Neuroevolution: Genetic Algorithms are a Competitive Alternative for Training Deep Neural Networks for Reinforcement Learning”

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These are my notes for chapter 2 of the Deep Learning book. They can also serve as a quick intro to linear algebra for deep learning.

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This post details my experience reproducing “Self-Normalizing Neural Networks” as part of the Nurture.AI NIPS Challenge 2017, as well as my experience participating in the challenge.

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This post details my experiments and implementations with three important loss functions for the Kaggle 2018 data science bowl, and compares their effects on a simplified implementation of U-Net.

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This is a reproduction of the metalearning paper “Learning to Learn by Gradient Descent by Gradient Descent”

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A tutorial on deep reinforcement learning, reproducing ‘Human-level control through deep reinforcement learning’

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A tutorial on deep reinforcement learning, reproducing ‘Playing Atari with Deep Reinforcement Learning’, which introduces the notion of a Deep Q-Network.

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The first post in my tutorial series on deep reinforcement learning, which introduces RL in general.

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