conftrace_

scalable inference

33 papers

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Co-occurring keywords

gaussian process (1200) variational inference (2069) bayesian inference (1907) posterior approximation (132) approximate inference (253) stochastic variational inference (59) latent variable model (564) generalized linear model (138) matrix multiplication (41) deep kernel (16)

Papers

Learning from Sibling Mentions with Scalable Graph Inference in Fine-Grained Entity Typing ACL 2022
Hybrid Autoregressive Inference for Scalable Multi-Hop Explanation Regeneration AAAI 2022
Scalable Gaussian Process Variational Autoencoders AISTATS 2021
SKIing on Simplices: Kernel Interpolation on the Permutohedral Lattice for Scalable Gaussian Processes ICML 2021
Scalable Gaussian Process Regression Networks IJCAI 2020
Inter-domain Deep Gaussian Processes ICML 2020
Scalable Exact Inference in Multi-Output Gaussian Processes ICML 2020
Exact Gaussian Processes on a Million Data Points NIPS 2019
Nonparametric Bayesian Aggregation for Massive Data JMLR 2019
SCAN: A Scalable Neural Networks Framework Towards Compact and Efficient Models NIPS 2019
Generic Inference in Latent Gaussian Process Models JMLR 2019
Embarrassingly Parallel Inference for Gaussian Processes JMLR 2019
Scalable Generalized Dynamic Topic Models AISTATS 2018
Scalable Gaussian Processes with Billions of Inducing Inputs via Tensor Train Decomposition AISTATS 2018
Product Kernel Interpolation for Scalable Gaussian Processes AISTATS 2018
Multimodal Prediction and Personalization of Photo Edits with Deep Generative Models AISTATS 2018
GPyTorch: Blackbox Matrix-Matrix Gaussian Process Inference with GPU Acceleration NIPS 2018
Scaling the Poisson GLM to massive neural datasets through polynomial approximations NIPS 2018
Learning Scalable Deep Kernels with Recurrent Structure JMLR 2017
Robust and Efficient Transfer Learning with Hidden Parameter Markov Decision Processes NIPS 2017
Scalable Variational Inference for Super Resolution Microscopy AISTATS 2017
PASS-GLM: polynomial approximate sufficient statistics for scalable Bayesian GLM inference NIPS 2017
Scalable MCMC for Mixed Membership Stochastic Blockmodels AISTATS 2016
d-VMP: Distributed Variational Message Passing PGM 2016
One-vs-Each Approximation to Softmax for Scalable Estimation of Probabilities NIPS 2016