Paper Summary - Assessing the Local Interpretability of Machine Learning Models by Slack et. al. (2019)
Summarizing and providing my notes on the paper - Assessing the Local Interpretability of Machine Learning Models by Slack et. al. (2019)
Summarizing and providing my notes on the paper - Assessing the Local Interpretability of Machine Learning Models by Slack et. al. (2019)
Summarizing and providing my notes on the paper - A review of possible effects of cognitive biases on interpretation of rule-based machine learning models by...
Summarizing and providing my notes on the paper - Synthesizing Interpretable Strategies for Solving Puzzle Games by Butler, Torlak & Popović (2017)
Summarizing and providing my notes on the paper - Programmatically Interpretable Reinforcement Learning by Verma et. al. (2018)
Summarizing and providing my notes on the paper - Distilling Deep Reinforcement Learning Policies in Soft Decision Trees by Coppens et. al. (2019)
Summarizing and providing my notes on the paper - Contrastive explanations for reinforcement learning in terms of expected consequences by van der Waa et. a...
Summarizing and providing my notes on the paper - Graying the black box: Understanding DQNs by Zahavy, Ben-Zrihem & Mannor (2016)
Summarizing and providing my notes on the paper - Improving Robot Controller Transparency Through Autonomous Policy Explanation by Hayes & Shah (2017)
Summarizing and providing my notes on the paper - Policy Distillation by Rusu et. al. (2016)
Summarizing and providing my notes on the paper - Toward Interpretable Deep Reinforcement Learning with Linear Model U-Trees by Liu et. al. (2018)
Summarizing and providing my notes on the paper - Explainable Reinforcement Learning Through a Causal Lens by Madumal et. al. (2020)
Summarizing and providing my notes on the paper - An Evaluation of the Human-Interpretability of Explanation by Lage et. al. (2019)
Summarizing and providing my notes on the paper - Programmatically Interpretable Reinforcement Learning by Verma et. al. (2018)
Summarizing and providing my notes on the paper - Distilling Deep Reinforcement Learning Policies in Soft Decision Trees by Coppens et. al. (2019)
Summarizing and providing my notes on the paper - Contrastive explanations for reinforcement learning in terms of expected consequences by van der Waa et. a...
Summarizing and providing my notes on the paper - Graying the black box: Understanding DQNs by Zahavy, Ben-Zrihem & Mannor (2016)
Summarizing and providing my notes on the paper - Improving Robot Controller Transparency Through Autonomous Policy Explanation by Hayes & Shah (2017)
Summarizing and providing my notes on the paper - Toward Interpretable Deep Reinforcement Learning with Linear Model U-Trees by Liu et. al. (2018)
Summarizing and providing my notes on the paper - Explainable Reinforcement Learning Through a Causal Lens by Madumal et. al. (2020)
Summarizing and providing my notes on the research talk - Human-AI Co-creation for Games and Game Creators by Mikhail Jacob (2021)
Summarizing and providing my notes on the research talk - Designer-friendly Machine Learning and Reinforcement Learning for Video Games by Adith Swaminathan ...
A retrospective on the problem-solving path that led to my first publication.
A retrospective of my time interning with Knexus Research, the problem I solved, and what I learned
An investigation into a curious implementataion detail of Python integer objects, and a quantitative explanation of the choices behind it.
A retrospective on the problem-solving path that led to my first publication.
Summarizing and providing my notes on the research talk - Human-AI Co-creation for Games and Game Creators by Mikhail Jacob (2021)
Summarizing and providing my notes on the research talk - Designer-friendly Machine Learning and Reinforcement Learning for Video Games by Adith Swaminathan ...
Summarizing and providing my notes on the talk - How to write a great research paper by Simon Peyton Jones (2016)
An editorial for the Dec ‘19 Div. 1 long contest on Codechef.
An editorial for the Nov ‘19 Div. 2 long contest on Codechef.
An editorial for the Dec ‘19 Div. 1 long contest on Codechef.
An editorial for the Nov ‘19 Div. 2 long contest on Codechef.
A retrospective of my time interning with Knexus Research, the problem I solved, and what I learned
A retrospective on the problem-solving path that led to my first publication.
Summarizing and providing my notes on the paper - A review of possible effects of cognitive biases on interpretation of rule-based machine learning models by...
Summarizing and providing my notes on the paper - Policy Distillation by Rusu et. al. (2016)
My notes from the Q&A by Gayle Laakman McDowell on Acing Programming Interviews
An editorial for the Nov ‘19 Div. 2 long contest on Codechef.
An editorial for the Dec ‘19 Div. 1 long contest on Codechef.
An investigation into a curious implementataion detail of Python integer objects, and a quantitative explanation of the choices behind it.
A retrospective of my time interning with Knexus Research, the problem I solved, and what I learned
A retrospective of my time interning with Knexus Research, the problem I solved, and what I learned
Summarizing and providing my notes on the paper - An Evaluation of the Human-Interpretability of Explanation by Lage et. al. (2019)
Summarizing and providing my notes on the paper - An Evaluation of the Human-Interpretability of Explanation by Lage et. al. (2019)
Summarizing and providing my notes on the paper - Hierarchical and Interpretable Skill Acquisition in Multi-Task Reinforcement Learning by Shu, Xiong & S...
Summarizing and providing my notes on the paper - Hierarchical and Interpretable Skill Acquisition in Multi-Task Reinforcement Learning by Shu, Xiong & S...
Summarizing and providing my notes on the talk - How to write a great research paper by Simon Peyton Jones (2016)
Summarizing and providing my notes on the paper - A review of possible effects of cognitive biases on interpretation of rule-based machine learning models by...
Attempting to use bipartite graphs to help Breaking Bad with its unique opening credits.
Attempting to use bipartite graphs to help Breaking Bad with its unique opening credits.
Attempting to use bipartite graphs to help Breaking Bad with its unique opening credits.