Most continual learning methods are validated in settings where task boundaries clearly defined and identity information is available during training testing. We explore how such perform a task-agnostic setting that more closely resembles dynamic clinical environments with gradual population shifts. propose ODEx, holistic solution combines out-of-distribution detection techniques. Validation on...

Countable state Markov shifts are a natural generalization of the well-known subshifts of finite type. They are the subject of current research both for their own sake and as models for smooth dynamical systems. In this paper, we investigate their almost isomorphism and entropy conjugacy and obtain a complete classification for the especially important class of strongly positive recurrent Marko...

Dynamic time warping is a simple classic method for aligning two sampled functions of time. The sequence of time shifts computed by this method are a globally optimal solution to a non-linear optimization problem with linear inequality constraints that may be directly related to subsurface properties. In applications to seismic traces, the time shifts may increase or decrease rapidly in time (a...