Results 11 to 20 of about 38,951,336 (344)
CrystalFlow: a flow-based generative model for crystalline materials [PDF]
Nat CommunDeep learning-based generative models hold significant promise for exploring the configuration space of crystalline materials, though their application remains in its early stages.
Xiao-Shan Luo +7 more
semanticscholar +2 more sources
A generative model for inorganic materials design [PDF]
NatureThe design of functional materials with desired properties is essential in driving technological advances in areas such as energy storage, catalysis and carbon capture1, 2–3.
Claudio Zeni +25 more
semanticscholar +2 more sources
InCoder: A Generative Model for Code Infilling and Synthesis [PDF]
International Conference on Learning Representations, 2022 Code is seldom written in a single left-to-right pass and is instead repeatedly edited and refined. We introduce InCoder, a unified generative model that can perform program synthesis (via left-to-right generation) as well as editing (via infilling ...
Daniel Fried +9 more
semanticscholar +1 more source
GET3D: A Generative Model of High Quality 3D Textured Shapes Learned from Images [PDF]
Neural Information Processing Systems, 2022 As several industries are moving towards modeling massive 3D virtual worlds, the need for content creation tools that can scale in terms of the quantity, quality, and diversity of 3D content is becoming evident. In our work, we aim to train performant 3D
Jun Gao +8 more
semanticscholar +1 more source
Lifelong generative modeling [PDF]
Neurocomputing, 2020 Lifelong learning is the problem of learning multiple consecutive tasks in a sequential manner, where knowledge gained from previous tasks is retained and used to aid future learning over the lifetime of the learner. It is essential towards the development of intelligent machines that can adapt to their surroundings. In this work we focus on a lifelong
Jason Ramapuram +2 more
openaire +5 more sources
Exposing flaws of generative model evaluation metrics and their unfair treatment of diffusion models [PDF]
Neural Information Processing Systems, 2023 We systematically study a wide variety of generative models spanning semantically-diverse image datasets to understand and improve the feature extractors and metrics used to evaluate them.
G. Stein +9 more
semanticscholar +1 more source
Survey of generative adversarial network
网络与信息安全学报, 2021 Firstly, the basic theory, application scenarios and current state of research of GAN (generative adversarial network) were introduced, and the problems need to be improved were listed. Then, recent research, improvement mechanism and model features in 2
WANG Zhenglong, ZHANG Baowen
doaj +1 more source
iPoLNG—An unsupervised model for the integrative analysis of single-cell multiomics data
Frontiers in Genetics, 2023 Single-cell multiomics technologies, where the transcriptomic and epigenomic profiles are simultaneously measured in the same set of single cells, pose significant challenges for effective integrative analysis. Here, we propose an unsupervised generative
Wenyu Zhang, Zhixiang Lin
doaj +1 more source
Sensors, 2021 Recently, most state-of-the-art anomaly detection methods are based on apparent motion and appearance reconstruction networks and use error estimation between generated and real information as detection features.
Tuan-Hung Vu +3 more
doaj +1 more source
Bacteriophage Genetic Edition Using LSTM
Frontiers in Bioinformatics, 2022 Bacteriophages are gaining increasing interest as antimicrobial tools, largely due to the emergence of multi-antibiotic–resistant bacteria. Although their huge diversity and virulence make them particularly attractive for targeting a wide range of ...
Shabnam Ataee +8 more
doaj +1 more source