214 citations · 487 across the 24 of their papers we have counts for
4 papers · 1 filter
Truncated Variational Sampling for "Black Box" Optimization of Generative Models
Jörg Lücke, Zhenwen Dai, Georgios Exarchakis
We investigate the optimization of two probabilistic generative models with binary latent variables using a novel variational EM approach. The approach distinguishes itself from pr…
Auto-Differentiating Linear Algebra
Matthias Seeger, Asmus Hetzel, Zhenwen Dai +2
Development systems for deep learning (DL), such as Theano, Torch, TensorFlow, or MXNet, are easy-to-use tools for creating complex neural network models. Since gradient computatio…
Efficient Modeling of Latent Information in Supervised Learning using Gaussian Processes
Zhenwen Dai, Mauricio A. Álvarez, Neil D. Lawrence
Often in machine learning, data are collected as a combination of multiple conditions, e.g., the voice recordings of multiple persons, each labeled with an ID. How could we build a…
Preferential Bayesian Optimization
Javier Gonzalez, Zhenwen Dai, Andreas Damianou +1
Bayesian optimization (BO) has emerged during the last few years as an effective approach to optimizing black-box functions where direct queries of the objective are expensive. In…