Results 1 to 10 of about 38,951,336 (344)
Application of SMILES-based molecular generative model in new drug design
Frontiers in Pharmacology, 2022 Weiya Kong +3 more
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CoRRReinforcement Learning from Human Feedback (RLHF) has greatly improved the performance of modern Large Language Models (LLMs). The RLHF process is resource-intensive and technically challenging, generally requiring a large collection of human preference labels over model-generated outputs.
Dakota Mahan +8 more
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COTIC: Embracing Non-Uniformity in Event Sequence Data via Multilayer Continuous Convolution
IEEE AccessIrregular event streams are common in domains such as finance, healthcare, and e-commerce, where the underlying data-generating processes are often highly complex and vary widely in scale. Models must adapt their temporal expressiveness while maintaining
Vladislav Zhuzhel +11 more
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Dianxin kexue, 2023 Recently, artificial intelligence generated content (AIGC) technology has achieved various disruptive results and has become a new trend in AI research and application, driving AI into a new era.Firstly, the development status of AIGC technology was ...
Zhe QIAO
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Generalizations of dual models
Nuclear Physics B, 1971 Generalizations of the dual model are discussed in the context of functional integral formulation of the theory. We notice that all the symmetries of dual amplitudes are led from the symmetries of the Lagrangian used for the measure of functional integration.
J.-L. GERVAIS, B. SAKITA
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Yantu gongcheng xuebaoAmid the accelerating transformation of the global energy structure, hydrogen energy, with its characteristics of abundant resources and zero carbon emissions, has emerged as a crucial part of China's energy development strategy.
LEI Huayang 1, 2, ZHANG Xinyu 1, XU Yinggang 1
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The Anatomy of Inference: Generative Models and Brain Structure
Frontiers in Computational Neuroscience, 2018 To infer the causes of its sensations, the brain must call on a generative (predictive) model. This necessitates passing local messages between populations of neurons to update beliefs about hidden variables in the world beyond its sensory samples.
Thomas Parr, Karl J. Friston
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Proceedings of the AAAI Conference on Artificial Intelligence, 2018 We propose a novel approach for using unsupervised boosting to create an ensemble of generative models, where models are trained in sequence to correct earlier mistakes. Our meta-algorithmic framework can leverage any existing base learner that permits likelihood evaluation, including recent deep expressive models. Further, our approach
Aditya Grover, Stefano Ermon
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Learnable Priors Support Reconstruction in Diffuse Optical Tomography
PhotonicsDiffuse Optical Tomography (DOT) is a non-invasive medical imaging technique that makes use of Near-Infrared (NIR) light to recover the spatial distribution of optical coefficients in biological tissues for diagnostic purposes.
Alessandra Serianni +2 more
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Virtual Magnetic Resonance Elastography Using a Deep Generative Model for Liver Fibrosis Staging
iRADIOLOGYBackground Liver biopsy is invasive, which presents many limitations in clinical settings. Magnetic resonance elastography (MRE) has significant value in non‐invasively diagnosing liver fibrosis. However, its use is currently uncommon because it requires
Longyu Sun +9 more
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