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Methods/Truncation Trick

Truncation Trick

GeneralIntroduced 2000136 papers

Description

The Truncation Trick is a latent sampling procedure for generative adversarial networks, where we sample $z$ from a truncated normal (where values which fall outside a range are resampled to fall inside that range). The original implementation was in Megapixel Size Image Creation with GAN. In BigGAN, the authors find this provides a boost to the Inception Score and FID.

Papers Using This Method

ParaGAN: A Scalable Distributed Training Framework for Generative Adversarial Networks2024-11-06 Unsupervised Panoptic Interpretation of Latent Spaces in GANs Using Space-Filling Vector Quantization2024-10-27 Feature Proliferation -- the "Cancer" in StyleGAN and its Treatments2023-10-13 On quantifying and improving realism of images generated with diffusion2023-09-26 Precision-Recall Divergence Optimization for Generative Modeling with GANs and Normalizing Flows2023-09-21 A Strategic Framework for Optimal Decisions in Football 1-vs-1 Shot-Taking Situations: An Integrated Approach of Machine Learning, Theory-Based Modeling, and Game Theory2023-07-27 Pyrus Base: An Open Source Python Framework for the RoboCup 2D Soccer Simulation2023-07-22 Diffusion Models Beat GANs on Image Classification2023-07-17 Diversity is Strength: Mastering Football Full Game with Interactive Reinforcement Learning of Multiple AIs2023-06-28 Rosetta Neurons: Mining the Common Units in a Model Zoo2023-06-15 Toward more accurate and generalizable brain deformation estimators for traumatic brain injury detection with unsupervised domain adaptation2023-06-08 FOOCTTS: Generating Arabic Speech with Acoustic Environment for Football Commentator2023-06-07 Action valuation of on- and off-ball soccer players based on multi-agent deep reinforcement learning2023-05-29 Is Centralized Training with Decentralized Execution Framework Centralized Enough for MARL?2023-05-27 Adaptive action supervision in reinforcement learning from real-world multi-agent demonstrations2023-05-22 An Empirical Study on Google Research Football Multi-agent Scenarios2023-05-16 The MuSe 2023 Multimodal Sentiment Analysis Challenge: Mimicked Emotions, Cross-Cultural Humour, and Personalisation2023-05-05 SportsMOT: A Large Multi-Object Tracking Dataset in Multiple Sports Scenes2023-04-11 VARS: Video Assistant Referee System for Automated Soccer Decision Making from Multiple Views2023-04-10 Towards Active Learning for Action Spotting in Association Football Videos2023-04-09