Results 81 to 90 of about 39,632 (294)
A De Novo Molecular Generation Method Using Latent Vector Based Generative Adversarial Network
, 2019 Deep learning methods applied to drug discovery have been used to generate novel structures. In this study, we propose a new deep learning architecture, LatentGAN, which combines an autoencoder and a generative adversarial neural network for de novo ...
Oleksii, Prykhodko +6 more
core +1 more source
Stable Imitation of Multigait and Bipedal Motions for Quadrupedal Robots Over Uneven Terrains
Advanced Robotics Research, EarlyView.How are quadrupedal robots empowered to execute complex navigation tasks, including multigait and bipedal motions? Challenges in stability and real‐world adaptation persist, especially with uneven terrains and disturbances. This article presents an imitation learning framework that enhances adaptability and robustness by incorporating long short‐term ...
Erdong Xiao +3 more
wiley +1 more source
Applied Sciences, 2023 This paper introduces a novel and robust data-driven algorithm designed for Aircraft Trajectory Prediction (ATP). The approach employs a Neural Network architecture to predict future aircraft trajectories, utilizing input variables such as latitude ...
Seyed Mohammad Hashemi +3 more
doaj +1 more source
Generative Multi-Adversarial Networks
CoRR, 2016 Generative adversarial networks (GANs) are a framework for producing a generative model by way of a two-player minimax game. In this paper, we propose the \emph{Generative Multi-Adversarial Network} (GMAN), a framework that extends GANs to multiple discriminators.
Ishan P. Durugkar +2 more
openaire +3 more sources
Quantum generative adversarial networks [PDF]
Physical Review A, 2018 10 pages, 8 ...
Pierre-Luc Dallaire-Demers +1 more
openaire +2 more sources
Information Transmission Strategies for Self‐Organized Robotic Aggregation
Advanced Robotics Research, EarlyView.In this review, we discuss how information transmission influences the neighbor‐based self‐organized aggregation of swarm robots. We focus specifically on local interactions regarding information transfer and categorize previous studies based on the functions of the information exchanged.
Shu Leng +5 more
wiley +1 more source
Conditional Wasserstein Generative Adversarial Network 를 활용한 메타표면 설계
, 2022 MasterAs a method for inverse design of metasurfaces, we propose a conditional Wasserstein generative adversarial network that combines the design idea of a conditional generative adversarial network with the optimization method of a Wasserstein ...
김선욱
core
Generative Adversarial Networks Unlearning
IEEE Transactions on Dependable and Secure ComputingAs machine learning continues to develop, and data misuse scandals become more prevalent, individuals are becoming increasingly concerned about their personal information and are advocating for the right to remove their data. Machine unlearning has emerged as a solution to erase training data from trained machine learning models. Despite its success in
Hui Sun +3 more
openaire +2 more sources
Generative Adversarial Mapping Networks
CoRR, 2017 9 pages, 7 ...
Jianbo Guo, Guangxiang Zhu, Jian Li
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Slimmable Generative Adversarial Networks
Proceedings of the AAAI Conference on Artificial Intelligence, 2021 Generative adversarial networks (GANs) have achieved remarkable progress in recent years, but the continuously growing scale of models make them challenging to deploy widely in practical applications. In particular, for real-time generation tasks, different devices require generators of different sizes due to varying computing power.
Liang Hou +5 more
openaire +2 more sources