Patrick Emami
My summaries of Machine Learning papers and investigations into various topics concerning artificial intelligence

Deep Reinforcement Learning


Recurrent Environment Simulators
// Chiappa, et. al., 2017








Variational Information Maximizing Exploration
// Houthooft, et al., 2016 ~ OpenAI


Deep Exploration via Bootstrapped DQN
// Osband, et al., 2016




Neural Fitted Q Iteration
// Riedmiller, M. 2005






Prioritized Experience Replay
// Schaul, Quan, Antonoglou, Silver, 2016


Incentivizing Exploration in Reinforcement Learning with Deep Predictive Models
// Bradly C. Stadie, Sergey Levine, Pieter Abbeel, 2015

Computer Vision




Pixel Recursive Super Resolution
// Dahl, Norouzi, Shlens, 2017



Reinforcement Learning Theory












Cooperative Inverse Reinforcement Learning
// Hadfield-Menell, et al., 2016

Generative Adversarial Networks





Natural Language Processing




A Neural Probabilistic Language Model
// Bengio, et. al., 2003

Deep Learning











General Artificial Intelligence





General Machine Learning






The Markov Chain Monte Carlo Revolution
// Persi Diaconis, 2009


Topology and Data
// Gunnar Carlsson, 2009






Intention-Aware Risk Estimation: Field Results
// Lefevre, Vasquez, Laugier, Ibanez-Guzman, 2015