Deep Learning
Log-Likelihood Ratio Minimizing Flows: Towards Robust and Quantifiable Neural Distribution Alignment Ben Usman
The variability of what "similar" means in this context, which transformations are allowed, and whether data points themselves or their feature representations
HAPI: A Large-scale Longitudinal Dataset of Commercial ML API Predictions
Commercial ML APIs offered by providers such as Google, Amazon and Microsoft have dramatically simplified ML adoption in many applications.
Robust Deep Reinforcement Learning against Adversarial Perturbations on State Observations
A deep reinforcement learning (DRL) agent observes its states through observations, which may contain natural measurement errors or adversarial noises.
EpiGRAF: Rethinking training of 3D GANs
But this solution comes at a cost: not only does it break multi-view consistency (i.e., shape and texture change when the camera moves),
