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Found 3 papers, 1 papers with code
Mutual Wasserstein Discrepancy Minimization for Sequential Recommendation
Wasserstein Discrepancy Measurement builds upon the 2-Wasserstein distance, which is more robust, more efficient in small batch sizes, and able to model the uncertainty of stochastic augmentation processes.
Time Lag Aware Sequential Recommendation
First, the existing methods often lack the simultaneous consideration of the global stability and local fluctuation of user preference, which might degrade the learning of a user's current preference.
Z-Order Recurrent Neural Networks for Video Prediction
First, we propose a new RNN architecture for modeling the deterministic dynamics, which updates hidden states along a z-order curve to enhance the consistency of the features of mirrored layers.
Ranked #1 on
Video Prediction
on KTH
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