Results 51 to 60 of about 715,782 (191)
Proceedings of the AAAI Conference on Artificial Intelligence, 2020 Modern methods for learning over graph input data have shown the fruitfulness of accounting for relationships among elements in a collection. However, most methods that learn over set input data use only rudimentary approaches to exploit intra-collection relationships.
Yifeng Shi +2 more
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Reactive Message Passing for Scalable Bayesian Inference [PDF]
, 2021 We introduce Reactive Message Passing (RMP) as a framework for executing schedule-free, robust and scalable message passing-based inference in a factor graph representation of a probabilistic model.
Vries, Bert de, Bagaev, Dmitry; id_orcid
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Approximate Message Passing Algorithm for Nonconvex Regularization
IEEE Access, 2019 In this paper, we study the sparse signal reconstruction with nonconvex regularization, mainly focusing on two popular nonconvex regularization methods, minimax concave penalty (MCP) and smoothly clipped absolute deviation (SCAD).
Hui Zhang +4 more
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Framelet Message Passing [PDF]
, 2023 Graph neural networks (GNNs) have achieved champion in wide applications. Neural message passing is a typical key module for feature propagation by aggregating neighboring features.
Zhou, Bingxin +3 more
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Rely-Guarantee Based Reasoning for Message-Passing Programs [PDF]
Scientific Annals of Computer Science, 2014 The difficulties of verifying concurrent programs lie in their inherent non-determinism and interferences. Rely-Guarantee reasoning is one useful approach to solve this problem for its capability in formally specifying inter- thread interferences ...
J. Lei, Z. Qiu
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Generalized Approximate Message Passing Detector for GSM-OTFS Systems
IEEE Access, 2022 Orthogonal Time Frequency Space (OTFS) as a two-dimensional modulation scheme designed in the delay-Doppler domain, is realized by inverse symplectic finite Fourier transform (ISFFT) and symplectic finite Fourier transform (SFFT), for combating the high ...
Tiebin Wang +5 more
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Evaluating message passing control techniques in Smalltalk [PDF]
, 1999 In a language like Smalltalk in which objects communicate only via message passing, message passing control is a fundamental tool for the analysis of object behavior (trace, spying) or for the definition of new semantics (asynchronous messages, proxy,...)
Stéphane Ducasse, Ducasse, Stéphane
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Convolutional Approximate Message-Passing [PDF]
IEEE Signal Processing Letters, 2020 This letter proposes a novel message-passing algorithm for signal recovery in compressed sensing. The proposed algorithm solves the disadvantages of approximate message-passing (AMP) and orthogonal/vector AMP, and realizes their advantages. AMP converges only in a limited class of sensing matrices while it has low complexity.
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Deeply Learning the Messages in Message Passing Inference
CoRR, 2015 Deep structured output learning shows great promise in tasks like semantic image segmentation. We proffer a new, efficient deep structured model learning scheme, in which we show how deep Convolutional Neural Networks (CNNs) can be used to estimate the messages in message passing inference for structured prediction with Conditional Random Fields (CRFs).
Guosheng Lin +3 more
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J. Mach. Learn. Res., 2005 Bayesian inference is now widely established as one of the principal foundations for machine learning. In practice, exact inference is rarely possible, and so a variety of approximation techniques have been developed, one of the most widely used being a deterministic framework called variational inference. In this paper we introduce Variational Message
Winn, John, Bishop, Christopher
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