Adversarial Localized Energy Network for Structured Prediction

No abstract is available for this paper.

• Publication year

  2020

• Venue

  AAAI Conference on Artificial Intelligence

• Publication date

  2020-04-03

• Fields of study

  Computer Science

• Identifiers
  DOI 10.1609/AAAI.V34I04.5982
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar

• No claims are published for this paper.

• No concepts are published for this paper.

• Foundations of Machine Learning

  2021cited by this paper
• MEGAN: Mixture of Experts of Generative Adversarial Networks for Multimodal Image Generation

  2018cited by this paper
• Learning Approximate Inference Networks for Structured Prediction

  2018influential reference
• GENERATIVE ADVERSARIAL NETS

  2018cited by this paper
• Dual Conditional GANs for Face Aging and Rejuvenation

  2018cited by this paper
• Wasserstein GAN

  2017cited by this paper
• Deep Value Networks Learn to Evaluate and Iteratively Refine Structured Outputs

  2017influential reference
• End-to-End Learning for Structured Prediction Energy Networks

  2017influential reference
• TensorFlow: Large-Scale Machine Learning on Heterogeneous Distributed Systems

  2016cited by this paper
• Multi-class Generative Adversarial Networks with the L2 Loss Function

  2016cited by this paper
• Input Convex Neural Networks

  2016cited by this paper
• Image-to-Image Translation with Conditional Adversarial Networks

  2016cited by this paper
• Conditional Random Fields as Recurrent Neural Networks

  2015cited by this paper
• Structured Prediction Energy Networks

  2015influential reference
• Deep Learning for Semantic Part Segmentation with High-Level Guidance

  2015cited by this paper
• Deep Generative Image Models using a Laplacian Pyramid of Adversarial Networks

  2015cited by this paper
• Learning shape priors for object segmentation via neural networks

  2015cited by this paper
• Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks

  2015cited by this paper
• Training Deep Neural Networks via Direct Loss Minimization

  2015cited by this paper
• Max-Margin Boltzmann Machines for Object Segmentation

  2014cited by this paper
• Learning Deep Structured Models

  2014cited by this paper
• Multi-Label Learning with Posterior Regularization

  2014influential reference
• Adam: A Method for Stochastic Optimization

  2014cited by this paper
• Augmenting CRFs with Boltzmann Machine Shape Priors for Image Labeling

  2013cited by this paper
• Exploring Compositional High Order Pattern Potentials for Structured Output Learning

  2013cited by this paper
• Multilabel Text Classification for Automated Tag Suggestion

  2008cited by this paper
• Labeled Faces in the Wild: A Database forStudying Face Recognition in Unconstrained Environments

  2008cited by this paper
• A Tutorial on Energy-Based Learning

  2006influential reference
• Learning to Segment

  2004cited by this paper

• Incorporating Inductive Biases to Energy-based Generative Models

  2025cites this paper
• Implicit Training of Inference Network Models for Structured Prediction

  2023influential citation
• Structured Prediction with Stronger Consistency Guarantees

  2023cites this paper
• Implicit Training of Energy Model for Structure Prediction

  2022cites this paper
• Flow-Based Spatio-Temporal Structured Prediction of Motion Dynamics

  2021cites this paper
• Generative Transition Mechanism to Image-to-Image Translation via Encoded Transformation

  2021cites this paper
• Automated Deepfake Detection

  2021cites this paper
• AGKD-BML: Defense Against Adversarial Attack by Attention Guided Knowledge Distillation and Bi-directional Metric Learning

  2021cites this paper
• Point Adversarial Self-Mining: A Simple Method for Facial Expression Recognition

  2020cites this paper