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11/29/2019
Efficient Approximate Inference with Walsh-Hadamard Variational Inference
Variational inference offers scalable and flexible tools to tackle intra...
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10/22/2019
Kernel computations from large-scale random features obtained by Optical Processing Units
Approximating kernel functions with random features (RFs)has been a succ...
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05/27/2019
Walsh-Hadamard Variational Inference for Bayesian Deep Learning
Over-parameterized models, such as DeepNets and ConvNets, form a class o...
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10/29/2018
Variational Calibration of Computer Models
Bayesian calibration of black-box computer models offers an established ...
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09/09/2016
Efficient batch-sequential Bayesian optimization with moments of truncated Gaussian vectors
We deal with the efficient parallelization of Bayesian global optimizati...
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03/18/2015