Natasha Jaques
Publications by Year
Research Areas
Reinforcement Learning in Robotics, Multimodal Machine Learning Applications, Topic Modeling, Adversarial Robustness in Machine Learning, Emotion and Mood Recognition
Most-Cited Works
- → Tackling Climate Change with Machine Learning(2022)781 cited
- → Automatic identification of artifacts in electrodermal activity data(2015)262 cited
- → Social Influence as Intrinsic Motivation for Multi-Agent Deep Reinforcement Learning(2018)262 cited
- → Personalized Multitask Learning for Predicting Tomorrow's Mood, Stress, and Health(2017)259 cited
- → Recognizing academic performance, sleep quality, stress level, and mental health using personality traits, wearable sensors and mobile phones(2015)239 cited
- → Predicting students' happiness from physiology, phone, mobility, and behavioral data(2015)135 cited
- → Predicting Affect from Gaze Data during Interaction with an Intelligent Tutoring System(2014)133 cited
- → Way Off-Policy Batch Deep Reinforcement Learning of Implicit Human Preferences in Dialog(2019)131 cited
- → Multimodal autoencoder: A deep learning approach to filling in missing sensor data and enabling better mood prediction(2017)121 cited