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Methodology
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Deep Learning
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Variational Inference
1946 directly classified papers
Papers per year
2005: 2
2006: 7
2007: 7
2008: 4
2009: 8
2010: 9
2011: 11
2012: 14
2013: 16
2014: 11
2015: 30
2016: 40
2017: 75
2018: 140
2019: 257
2020: 250
2021: 275
2022: 253
2023: 233
2024: 146
2025: 103
2026: 55
Papers
HOT-VAE: Learning High-Order Label Correlation for Multi-Label Classification via Attention-Based Variational Autoencoders
AAAI 2021
StyleMeUp: Towards Style-Agnostic Sketch-Based Image Retrieval
CVPR 2021
Trumpets: Injective flows for inference and inverse problems
UAI 2021
NP-DRAW: A Non-Parametric Structured Latent Variable Model for Image Generation
UAI 2021
Learning proposals for probabilistic programs with inference combinators
UAI 2021
GP-ConvCNP: Better generalization for conditional convolutional Neural Processes on time series data
UAI 2021
Content Learning with Structure-Aware Writing: A Graph-Infused Dual Conditional Variational Autoencoder for Automatic Storytelling
AAAI 2021
Unbiased gradient estimation for variational auto-encoders using coupled Markov chains
UAI 2021
Variational inference with continuously-indexed normalizing flows
UAI 2021
Physarum Powered Differentiable Linear Programming Layers and Applications
AAAI 2021
Probing Product Description Generation via Posterior Distillation
AAAI 2021
Synergetic Learning of Heterogeneous Temporal Sequences for Multi-Horizon Probabilistic Forecasting
AAAI 2021
Statistical Regeneration Guarantees of the Wasserstein Autoencoder with Latent Space Consistency
NIPS 2021
Deep Probabilistic Canonical Correlation Analysis
AAAI 2021
Neural Attention-Aware Hierarchical Topic Model
EMNLP 2021
Event Representation with Sequential, Semi-Supervised Discrete Variables
NAACL 2021
Accelerating Continuous Normalizing Flow with Trajectory Polynomial Regularization
AAAI 2021
Rectangular Flows for Manifold Learning
NIPS 2021
Temporal Latent Auto-Encoder: A Method for Probabilistic Multivariate Time Series Forecasting
AAAI 2021
SHOT-VAE: Semi-supervised Deep Generative Models With Label-aware ELBO Approximations
AAAI 2021
Semi-Supervised Learning with Variational Bayesian Inference and Maximum Uncertainty Regularization
AAAI 2021
Open-Set Recognition with Gaussian Mixture Variational Autoencoders
AAAI 2021
Neural Latent Space Model for Dynamic Networks and Temporal Knowledge Graphs
AAAI 2021
Multi-stream based marked point process
ACML 2021
Generalized Zero-Shot Learning via Disentangled Representation
AAAI 2021
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