Research map / Probabilistic and scientific modeling / Variational and generative sampling
Adversarially-learned Inference via an Ensemble of Discrete Undirected Graphical Models
Read the paperCheck your idea against 108,967 papers
AI-extracted summary. Written by AI from the paper's title only (no summary yet). Numbers and claims can be wrong or missing context, so check the paper before you cite or build on it.
Closest papers by meaning
- GibbsNet: Iterative Adversarial Inference for Deep Graphical Models (NeurIPS 2017 · similarity 0.89)
- Generalized Adversarially Learned Inference (AAAI 2021 · similarity 0.88)
- Adversarially Learned Inference (ICLR 2017 · similarity 0.86)
- Composing graphical models with neural networks for structured representations and fast inference (NeurIPS 2016 · similarity 0.85)
- SGAN: An Alternative Training of Generative Adversarial Networks (CVPR 2018 · similarity 0.85)
- On Neural Networks as Infinite Tree-Structured Probabilistic Graphical Models (NeurIPS 2024 · similarity 0.84)
Writing a paper in this area? scime draft is a free LaTeX editor with AI included, real-time co-authors and a check of your references and venue rules before you submit. It also imports OpenAI Prism projects.