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Found 3 papers, 1 papers with code
On the Value of Infinite Gradients in Variational Autoencoder Models
A number of recent studies of continuous variational autoencoder (VAE) models have noted, either directly or indirectly, the tendency of various parameter gradients to drift towards infinity during training.
GRIN: Generative Relation and Intention Network for Multi-agent Trajectory Prediction
Learning the distribution of future trajectories conditioned on the past is a crucial problem for understanding multi-agent systems.
Learning deep kernels for exponential family densities
The kernel exponential family is a rich class of distributions, which can be fit efficiently and with statistical guarantees by score matching.
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