Erik Bodin

Publication Activity (10 Years)

Years Active: 2017-2021
Publications (10 Years): 11

Top Topics

Recursive Partitioning

Deep Belief Networks

Hyperparameters

Gaussian Process

Top Venues

Publications

Erik Bodin, Federico Tomasi, Zhenwen Dai
Making Differentiable Architecture Search less local. CoRR (2021)
Erik Bodin, Zhenwen Dai, Neill W. Campbell, Carl Henrik Ek
Black-box density function estimation using recursive partitioning. ICML (2021)
Erik Bodin, Markus Kaiser, Ieva Kazlauskaite, Zhenwen Dai, Neill W. Campbell, Carl Henrik Ek
Modulating Surrogates for Bayesian Optimization. ICML (2020)
Erik Bodin, Zhenwen Dai, Neill D. F. Campbell, Carl Henrik Ek
Black-box density function estimation using recursive partitioning. CoRR (2020)
Ivan Ustyuzhaninov, Ieva Kazlauskaite, Markus Kaiser, Erik Bodin, Neill D. F. Campbell, Carl Henrik Ek
Compositional uncertainty in deep Gaussian processes. UAI (2020)
Erik Bodin, Markus Kaiser, Ieva Kazlauskaite, Neill D. F. Campbell, Carl Henrik Ek
Modulated Bayesian Optimization using Latent Gaussian Process Models. CoRR (2019)
Ivan Ustyuzhaninov, Ieva Kazlauskaite, Markus Kaiser, Erik Bodin, Neill D. F. Campbell, Carl Henrik Ek
Compositional uncertainty in deep Gaussian processes. CoRR (2019)
Alessandro Di Martino, Erik Bodin, Carl Henrik Ek, Neill D. F. Campbell
Gaussian Process Deep Belief Networks: A Smooth Generative Model of Shape with Uncertainty Propagation. ACCV (4) (2018)
Alessandro Di Martino, Erik Bodin, Carl Henrik Ek, Neill D. F. Campbell
Gaussian Process Deep Belief Networks: A Smooth Generative Model of Shape with Uncertainty Propagation. CoRR (2018)
Erik Bodin, Iman Malik, Carl Henrik Ek, Neill D. F. Campbell
Nonparametric Inference for Auto-Encoding Variational Bayes. CoRR (2017)
Erik Bodin, Neill D. F. Campbell, Carl Henrik Ek
Latent Gaussian Process Regression. CoRR (2017)