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Neil D. Lawrence

29 papers · 2006–2022 · 6 conferences · across top CS/AI conferences

Achievements

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+11 more ↓ 🧭 Keyword Pioneer πŸŒ‰ Interdisciplinary Bridge 🌈 Renaissance Researcher (7) πŸ—ΊοΈ Taxonomy Completionist (19) 🐣 Hot Topic Early Bird
πŸƒ Academic Marathon (16) 🧭 Keyword Pioneer 🌍 Conference Polyglot (6) 🌟 Keyword Trendsetter Combo (6) πŸ”¬ Deep Specialist (14) πŸ† Keyword Champion (5) πŸ’Ž Century Club (29) πŸ“ˆ Trend Setter πŸš€ Conference Pioneer πŸ”₯ Unstoppable (5) πŸ—ƒοΈ Keyword Collector (76)

Conferences

AISTATS (9) NIPS (9) JMLR (6) ICML (3) CVPR (1) ICLR (1)

Papers

Two-way Sparse Network Inference for Count Data AISTATS 2022 Generalised GPLVM with Stochastic Variational Inference AISTATS 2022 Modeling the Machine Learning Multiverse NIPS 2022 Differentially Private Regression and Classification with Sparse Gaussian Processes JMLR 2021 Multi-view Learning as a Nonparametric Nonlinear Inter-Battery Factor Analysis JMLR 2021 Transferring Knowledge across Learning Processes ICLR 2019 Variational Information Distillation for Knowledge Transfer CVPR 2019 Differentially Private Regression with Gaussian Processes AISTATS 2018 Structured Variationally Auto-encoded Optimization ICML 2018 Preferential Bayesian Optimization ICML 2017 Chained Gaussian Processes AISTATS 2016 Variational Inference for Latent Variables and Uncertain Inputs in Gaussian Processes JMLR 2016 Hybrid Discriminative-Generative Approach with Gaussian Processes AISTATS 2014 Tilted Variational Bayes AISTATS 2014 Deep Gaussian Processes AISTATS 2013 The Bigraphical Lasso ICML 2013 Fast Variational Inference in the Conjugate Exponential Family NIPS 2012 A Unifying Probabilistic Perspective for Spectral Dimensionality Reduction: Insights and New Models JMLR 2012 Computationally Efficient Convolved Multiple Output Gaussian Processes JMLR 2011 Variational Gaussian Process Dynamical Systems NIPS 2011 Efficient inference in matrix-variate Gaussian models with \iid observation noise NIPS 2011 Efficient Multioutput Gaussian Processes through Variational Inducing Kernels AISTATS 2010 Switched Latent Force Models for Movement Segmentation NIPS 2010 Bayesian Gaussian Process Latent Variable Model AISTATS 2010 Efficient Sampling for Gaussian Process Inference using Control Variables NIPS 2008 Accelerating Bayesian Inference over Nonlinear Differential Equations with Gaussian Processes NIPS 2008 Sparse Convolved Gaussian Processes for Multi-output Regression NIPS 2008 Modelling transcriptional regulation using Gaussian Processes NIPS 2006 Optimising Kernel Parameters and Regularisation Coefficients for Non-linear Discriminant Analysis JMLR 2006