conftrace_

gaussian process

1200 papers

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Also known as

GP

Co-occurring keywords

variational inference (2069) bayesian optimization (624) bayesian inference (1907) uncertainty quantification (1393) kernel methods (1097) gaussian processes (89) regret bound (1926) active learning (1301) sparse approximation (76) hyperparameter optimization (406)

Papers

Variational Inference for Gaussian Process Models with Linear Complexity NIPS 2017
Deep Multi-task Gaussian Processes for Survival Analysis with Competing Risks NIPS 2017
GPflow: A Gaussian Process Library using TensorFlow JMLR 2017
Probabilistic Line Searches for Stochastic Optimization JMLR 2017
Excess Risk Bounds for the Bayes Risk using Variational Inference in Latent Gaussian Models NIPS 2017
Cross-Spectral Factor Analysis NIPS 2017
Learning from Clinical Judgments: Semi-Markov-Modulated Marked Hawkes Processes for Risk Prognosis ICML 2017
Forecast the Plausible Paths in Crowd Scenes IJCAI 2017
Variational Mixtures of Gaussian Processes for Classification IJCAI 2017
Semantic Visualization for Short Texts with Word Embeddings IJCAI 2017
Learning Dynamics Across Similar Spatiotemporally-Evolving Physical Systems CORL 2017
Modelling Representation Noise in Emotion Analysis using Gaussian Processes IJCNLP 2017
Batched High-dimensional Bayesian Optimization via Structural Kernel Learning ICML 2017
Regret for Expected Improvement over the Best-Observed Value and Stopping Condition ACML 2017
Data-Efficient Reinforcement Learning in Continuous State-Action Gaussian-POMDPs NIPS 2017
Safe Model-based Reinforcement Learning with Stability Guarantees NIPS 2017
Max-value Entropy Search for Efficient Bayesian Optimization ICML 2017
Lower Bounds on Regret for Noisy Gaussian Process Bandit Optimization COLT 2017
Targeting EEG/LFP Synchrony with Neural Nets NIPS 2017
Efficient Modeling of Latent Information in Supervised Learning using Gaussian Processes NIPS 2017
Learning Kernels over Strings using Gaussian Processes IJCNLP 2017
Variational Bayesian Multiple Instance Learning With Gaussian Processes CVPR 2017
Scalable Log Determinants for Gaussian Process Kernel Learning NIPS 2017
Batched Gaussian Process Bandit Optimization via Determinantal Point Processes NIPS 2016
Automatic Construction of Nonparametric Relational Regression Models for Multiple Time Series ICML 2016