Papers
2,605 papers found
Computation-Aware Learning for Stable Control with Gaussian Process
Wenhan Cao, Alexandre Capone, Rishabh Yadav et al.
GM-CTSC at SemEval-2020 Task 1: Gaussian Mixtures Cross Temporal Similarity Clustering
Pierluigi Cassotti, Annalina Caputo, Marco Polignano et al.
RIJP at SemEval-2020 Task 1: Gaussian-based Embeddings for Semantic Change Detection
Ran Iwamoto, Masahiro Yukawa
UoR at SemEval-2020 Task 8: Gaussian Mixture Modelling (GMM) Based Sampling Approach for Multi-modal Memotion Analysis
Zehao Liu, Emmanuel Osei-Brefo, Siyuan Chen et al.
Subspace Inference for Bayesian Deep Learning
Pavel Izmailov, Wesley J. Maddox, Polina Kirichenko et al.
Compositional uncertainty in deep Gaussian processes
Ivan Ustyuzhaninov, Ieva Kazlauskaite, Markus Kaiser et al.
GPIRT: A Gaussian Process Model for Item Response Theory
JBrandon Duck-Mayr, Roman Garnett, Jacob Montgomery
An Interpretable and Sample Efficient Deep Kernel for Gaussian Process
Yijue Dai, Tianjian Zhang, Zhidi Lin et al.
Batch simulations and uncertainty quantification in Gaussian process surrogate approximate Bayesian computation
Marko Jarvenpaa, Aki Vehtari, Pekka Marttinen
Sensor Placement for Spatial Gaussian Processes with Integral Observations
Krista Longi, Chang Rajani, Tom Sillanpää et al.
Bayesian streaming sparse Tucker decomposition
Shikai Fang, Robert M. Kirby, Shandian Zhe
Scaling Hamiltonian Monte Carlo inference for Bayesian neural networks with symmetric splitting
Adam D. Cobb, Brian Jalaian
Probabilistic selection of inducing points in sparse Gaussian processes
Anders Kirk Uhrenholt, Valentin Charvet, Bjørn Sand Jensen
Gaussian process nowcasting: application to COVID-19 mortality reporting
Iwona Hawryluk, Henrique Hoeltgebaum, Swapnil Mishra et al.
Similarity measure for sparse time course data based on Gaussian processes
Zijing Liu, Mauricio Barahona
Subset-of-data variational inference for deep Gaussian-processes regression
Ayush Jain, P. K. Srijith, Mohammad Emtiyaz Khan
Learning to learn with Gaussian processes
Quoc Phong Nguyen, Bryan Kian Hsiang Low, Patrick Jaillet
Multi-output Gaussian Processes for uncertainty-aware recommender systems
Yinchong Yang, Florian Buettner
Information theoretic meta learning with Gaussian processes
Michalis K. Titsias, Francisco J. R. Ruiz, Sotirios Nikoloutsopoulos et al.
Combining pseudo-point and state space approximations for sum-separable Gaussian Processes
Will Tebbutt, Arno Solin, Richard E. Turner
Class balancing GAN with a classifier in the loop
Harsh Rangwani, Konda Reddy Mopuri, R. Venkatesh Babu
Learning in Multi-Player Stochastic Games
William Brown
Bayesian structure learning with generative flow networks
Tristan Deleu, António Góis, Chris Emezue et al.
Bayesian spillover graphs for dynamic networks
Grace Deng, David S. Matteson