Balaji Lakshminarayanan
5 papers in the PaperMetrix corpus
Papers by this author
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Kernel-Based Just-In-Time Learning for Passing Expectation Propagation Messages
2015 · arXiv (Cornell University)
We propose an efficient nonparametric strategy for learning a message operator in expectation propagation (EP), which takes as input the set of incoming messages to a factor node, and produces an outgoing message as output. …
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Simple and Scalable Predictive Uncertainty Estimation using Deep\n Ensembles
2016 · arXiv (Cornell University)
Deep neural networks (NNs) are powerful black box predictors that have\nrecently achieved impressive performance on a wide spectrum of tasks.\nQuantifying predictive uncertainty in NNs is a challenging and yet unsolved\nproblem. Bayesian NNs, which learn a …
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Bayesian Deep Ensembles via the Neural Tangent Kernel
2020 · arXiv (Cornell University)
We explore the link between deep ensembles and Gaussian processes (GPs) through the lens of the Neural Tangent Kernel (NTK): a recent development in understanding the training dynamics of wide neural networks (NNs). Previous work …
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Distributed Bayesian Learning with Stochastic Natural-gradient\n Expectation Propagation and the Posterior Server
2015 · arXiv (Cornell University)
This paper makes two contributions to Bayesian machine learning algorithms.\nFirstly, we propose stochastic natural gradient expectation propagation (SNEP),\na novel alternative to expectation propagation (EP), a popular variational\ninference algorithm. SNEP is a black box variational algorithm, …
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Gemini: A Family of Highly Capable Multimodal Models
2023 · arXiv (Cornell University)
This report introduces a new family of multimodal models, Gemini, that exhibit remarkable capabilities across image, audio, video, and text understanding. The Gemini family consists of Ultra, Pro, and Nano sizes, suitable for applications ranging …