Industry
Attentive State-Space Modeling of Disease Progression
Ahmed M. Alaa, Mihaela van der Schaar
Models of disease progression are instrumental forpredictingpatient outcomes and understandingdisease dynamics. Existing models provide the patient with pragmatic (supervised) predictions of risk, but do not provide the clinician with intelligible (unsupervised) representations ofdiseasepathology.
Invariance-inducing regularization using worst-case transformations suffices to boost accuracy and spatial robustness
Fanny Yang, Zuowen Wang, Christina Heinze-Deml
Neural Information Processing Systems http://nips.cc/
MixMatch: A Holistic Approach to Semi-Supervised Learning
David Berthelot, Nicholas Carlini, Ian Goodfellow, Nicolas Papernot, Avital Oliver, Colin A. Raffel
Neural Information Processing Systems http://nips.cc/