Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Importance Weighted Adversarial Variational Autoencoders for Spike
  Inference from Calcium Imaging Data   The Importance Weighted Auto Encoder (IWAE) objective has been shown to
improve the training of generative models over the standard Variational Auto
Encoder (VAE) objective. Here, we derive importance weighted extensions to AVB
and AAE. These latent variable models use implicitly defined inference networks
whose approximate posterior density q_\phi(z|x) cannot be directly evaluated,
an essential ingredient for importance weighting. We show improved training and
inference in latent variable models with our adversarially trained importance
weighting method, and derive new theoretical connections between adversarial
generative model training criteria and marginal likelihood based methods. We
apply these methods to the important problem of inferring spiking neural
activity from calcium imaging data, a challenging posterior inference problem
in neuroscience, and show that posterior samples from the adversarial methods
outperform factorized posteriors used in VAEs.

15
The categories of this paper are: nucl-ex
28
The categories of this paper are: alg-geom
21
The categories of this paper are: adap-org
6
The categories of this paper are: astro-ph
35
The categories of this paper are: mtrl-th
36
The categories of this paper are: cmp-lg
12
The categories of this paper are: nucl-th
22
The categories of this paper are: chao-dyn
32
The categories of this paper are: atom-ph
9
The categories of this paper are: nlin
11
The categories of this paper are: hep-lat
0
The categories of this paper are: hep-ph
8
The categories of this paper are: hep-ex
23
The categories of this paper are: solv-int
17
The categories of this paper are: q-fin
27
The categories of this paper are: comp-gas