Results 31 to 40 of about 24,500,069 (341)
Predictability and Surprise in Large Generative Models [PDF]
Conference on Fairness, Accountability and Transparency, 2022 Large-scale pre-training has recently emerged as a technique for creating capable, general-purpose, generative models such as GPT-3, Megatron-Turing NLG, Gopher, and many others.
Deep Ganguli +29 more
semanticscholar +1 more source
Kompren: modeling and generating model slicers [PDF]
Software & Systems Modeling, 2012 Among model comprehension tools, model slicers are tools that extract a subset of model elements, for a specific purpose. Model slicers provide a mechanism to isolate and focus on parts of the model, thereby improving the overall analysis process. However, existing slicers are dedicated to a specific modeling language.
Blouin, Arnaud +3 more
openaire +1 more source
Speech Enhancement with Score-Based Generative Models in the Complex STFT Domain [PDF]
Interspeech, 2022 Score-based generative models (SGMs) have recently shown impressive results for difficult generative tasks such as the unconditional and conditional generation of natural images and audio signals. In this work, we extend these models to the complex short-
Simon Welker +2 more
semanticscholar +1 more source
Multimeasurement Generative Models
CoRR, 2021 Our code is publicly available at https://github.com/nnaisense ...
Saeed Saremi, Rupesh Kumar Srivastava
openaire +3 more sources
Deep Generative Models Enable Navigation in Sparsely Populated Chemical Space
, 2021 Deep generative models are powerful tools for the exploration of chemical space, enabling the on-demand gener- ation of molecules with desired physical, chemical, or biological properties.
R. Greg, Stacey +3 more
core +1 more source
Deep generative models in DataSHIELD
BMC Medical Research Methodology, 2021 Background The best way to calculate statistics from medical data is to use the data of individual patients. In some settings, this data is difficult to obtain due to privacy restrictions.
Stefan Lenz, Moritz Hess, Harald Binder
doaj +1 more source
NeuroImage, 2023 Generative models of the human connectome enable in silico generation of brain networks based on probabilistic wiring rules. These wiring rules are governed by a small number of parameters that are typically fitted to individual connectomes and quantify ...
Yuanzhe Liu +6 more
doaj +1 more source
Comparative Study of Deep Generative Models on Chemical Space Coverage (v18)
, 2021 In recent years, deep molecular generative models have emerged as novel methods for de novo molecular design. Thanks to the rapid advance of deep learning techniques, deep learning architectures such as recurrent neural networks, generative autoencoders,
Rocío, Mercado +3 more
core +1 more source
Exploring generative artificial intelligence: a comprehensive guide [PDF]
PeerJ Computer ScienceGenerative artificial intelligence (GAI), a specialized branch of artificial intelligence, has developed as a dynamic discipline that drives innovation and creativity across several domains.
Rasha Shoitan +4 more
doaj +2 more sources
Probabilistic generative transformer language models for generative design of molecules
Journal of Cheminformatics, 2023 Self-supervised neural language models have recently found wide applications in the generative design of organic molecules and protein sequences as well as representation learning for downstream structure classification and functional prediction. However,
Lai Wei +4 more
doaj +1 more source