Neural Continuous-Discrete State Space Models for Irregularly-Sampled Time Series
We develop a family of stable continuous-time neural state space-models.
Abdul Fatir Ansari
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Deep Explicit Duration Switching Models for Time Series
We propose a deep switching state space model that can capture both state-dependent and time-dependent switching patterns in time series data.
A characteristic function approach to deep implicit generative modeling
We present a new method for training GANs via characteristic functions