Deep Learning
How Would The Viewer Feel? Estimating Wellbeing From Video Scenarios
Mantas Mazeika, Eric Tang, Andy Zou, Steven Basart, Jun Shern Chan, Dawn Song, David Forsyth, Jacob Steinhardt, Dan Hendrycks
In recent years, deep neural networks have demonstrated increasingly strong abilities to recognize objects and activities in videos.
neurips2022
Knowledge tracing (KT) is the task of using students' historical learning interaction data to model their knowledge mastery over time so as to make predictions on their
AdvFlow: Inconspicuous Black-box Adversarial Attacks using Normalizing Flows
In this regard, the design of stronger adversarial attacks plays a crucial role in understanding the nature of possible real-world threats.
On Scrambling Phenomena for Randomly Initialized Recurrent Networks
Recurrent Neural Networks (RNNs) frequently exhibit complicated dynamics, and their sensitivity to the initialization process often renders them notoriously hard to train.
