Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: PredRNN: A Recurrent Neural Network for Spatiotemporal Predictive
  Learning   The predictive learning of spatiotemporal sequences aims to generate future
images by learning from the historical context, where the visual dynamics are
believed to have modular structures that can be learned with compositional
subsystems. This paper models these structures by presenting PredRNN, a new
recurrent network, in which a pair of memory cells are explicitly decoupled,
operate in nearly independent transition manners, and finally form unified
representations of the complex environment. Concretely, besides the original
memory cell of LSTM, this network is featured by a zigzag memory flow that
propagates in both bottom-up and top-down directions across all layers,
enabling the learned visual dynamics at different levels of RNNs to
communicate. It also leverages a memory decoupling loss to keep the memory
cells from learning redundant features. We further propose a new curriculum
learning strategy to force PredRNN to learn long-term dynamics from context
frames, which can be generalized to most sequence-to-sequence models. We
provide detailed ablation studies to verify the effectiveness of each
component. Our approach is shown to obtain highly competitive results on five
datasets for both action-free and action-conditioned predictive learning
scenarios.

10
The categories of this paper are: q-bio
11
The categories of this paper are: hep-lat
21
The categories of this paper are: adap-org
12
The categories of this paper are: nucl-th
23
The categories of this paper are: solv-int
14
The categories of this paper are: math-ph
19
The categories of this paper are: eess
4
The categories of this paper are: cond-mat
22
The categories of this paper are: chao-dyn
7
The categories of this paper are: hep-th
13
The categories of this paper are: quant-ph
9
The categories of this paper are: nlin
17
The categories of this paper are: q-fin
26
The categories of this paper are: bayes-an
8
The categories of this paper are: hep-ex
28
The categories of this paper are: alg-geom