Robuta

Sponsor of the Day: Jerkmate
https://papers.nips.cc/paper_files/paper/2018/hash/b865367fc4c0845c0682bd466e6ebf4c-Abstract.html Infinite-Horizon Gaussian Processes infinite horizongaussian processes https://www.semanticscholar.org/search?q=Non-asymptotic+approximations+of+neural+networks+by+Gaussian+processes. Non-asymptotic approximations of neural networks by Gaussian processes. | Semantic Scholar An academic search engine that utilizes artificial intelligence methods to provide highly relevant results and novel tools to filter them with ease. processes semantic scholarneural networksnonasymptoticapproximations https://arxiv.org/abs/2112.10334 [2112.10334] Gaussian Processes for Finite Size Extrapolation of Many-Body Simulations Abstract page for arXiv paper 2112.10334: Gaussian Processes for Finite Size Extrapolation of Many-Body Simulations gaussian processesmany body2112finitesize https://arxiv.org/abs/1705.08933 [1705.08933] Doubly Stochastic Variational Inference for Deep Gaussian Processes Abstract page for arXiv paper 1705.08933: Doubly Stochastic Variational Inference for Deep Gaussian Processes gaussian processes1705doublystochasticvariational https://openreview.net/forum?id=oJp7uTL7ox- Gray-Box Gaussian Processes for Automated Reinforcement Learning | OpenReview Despite having achieved spectacular milestones in an array of important real-world applications, most Reinforcement Learning (RL) methods are very brittle... gaussian processesreinforcement learninggrayboxautomated https://deepgram.com/ai-glossary/gaussian-processes Gaussian Processes Ever pondered how machines learn to make sense of complex data, or how financial analysts forecast market trends with remarkable accuracy? In this article, we... gaussian processes https://www.deisenroth.cc/publication/souza-2025/ Infinite Neural Operators: Gaussian Processes on Functions | Marc Deisenroth Dec 4, 2025 - A variety of infinitely wide neural architectures (e.g., dense NNs, CNNs, and transformers) induce Gaussian process (GP) priors over their outputs. These... gaussian processesmarc deisenrothinfiniteneuraloperators https://ieeexplore.ieee.org/document/735807/ Bayesian classification with Gaussian processes | IEEE Journals & Magazine | IEEE Xplore We consider the problem of assigning an input vector to one of m classes by predicting P(c|x) for c=1,...,m. For a two-class problem, the probability of class o ieee journals magazinegaussian processesbayesianclassificationxplore https://scikit-learn.org/stable/modules/gaussian_process.html 1.7. Gaussian Processes — scikit-learn 1.8.0 documentation Gaussian Processes (GP) are a nonparametric supervised learning method used to solve regression and probabilistic classification problems. The advantages of... scikit learn 81 7gaussian processes0 documentation https://www.sandia.gov/research/publications/details/bayesian-learning-with-gaussian-processes-for-low-dimensional-representatio-2025-05-01/ Bayesian learning with Gaussian processes for low-dimensional representations of time-dependent... bayesian learninggaussian processeslow dimensionaltime dependentrepresentations https://cmjt.r-universe.dev/stelfi stelfi: Hawkes and Log-Gaussian Cox Point Processes Using Template Model Builder processes usingtemplate modelhawkesloggaussian