4.4k citations · 6.2k across the 79 of their papers we have counts for
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Variational Integrator Networks for Physically Structured Embeddings
Steindor Saemundsson, Alexander Terenin, Katja Hofmann +1
Learning workable representations of dynamical systems is becoming an increasingly important problem in a number of application areas. By leveraging recent work connecting deep neu…
Deep Gaussian Processes with Importance-Weighted Variational Inference
Hugh Salimbeni, Vincent Dutordoir, James Hensman +1
Deep Gaussian processes (DGPs) can model complex marginal densities as well as complex mappings. Non-Gaussian marginals are essential for modelling real-world data, and can be gene…
Differentially Private Empirical Risk Minimization with Sparsity-Inducing Norms
K S Sesh Kumar, Marc Peter Deisenroth
Differential privacy is concerned about the prediction quality while measuring the privacy impact on individuals whose information is contained in the data. We consider differentia…
High-dimensional Bayesian optimization using low-dimensional feature spaces
Riccardo Moriconi, Marc P. Deisenroth, K. S. Sesh Kumar
Bayesian optimization (BO) is a powerful approach for seeking the global optimum of expensive black-box functions and has proven successful for fine tuning hyper-parameters of mach…