Ieva Kazlauskaite

Publication Activity (10 Years)

Years Active: 2018-2024
Publications (10 Years): 19

Top Topics

Dirichlet Process

Gaussian Process

Inverse Problems

Top Venues

J. Comput. Phys.

Publications

Thomas A. Archbold, Ieva Kazlauskaite, Fehmi Cirak
Variational Bayesian surrogate modelling with application to robust design optimisation. CoRR (2024)
Arnaud Vadeboncoeur, Ieva Kazlauskaite, Yanni Papandreou, Fehmi Cirak, Mark Girolami, Ömer Deniz Akyildiz
Random Grid Neural Processes for Parametric Partial Differential Equations. CoRR (2023)
Arnaud Vadeboncoeur, Ieva Kazlauskaite, Yanni Papandreou, Fehmi Cirak, Mark Girolami, Ömer Deniz Akyildiz
Random Grid Neural Processes for Parametric Partial Differential Equations. ICML (2023)
Arnaud Vadeboncoeur, Ömer Deniz Akyildiz, Ieva Kazlauskaite, Mark Girolami, Fehmi Cirak
Fully probabilistic deep models for forward and inverse problems in parametric PDEs. J. Comput. Phys. 491 (2023)
Mala Virdee, Markus Kaiser, Emily Shuckburgh, Carl Henrik Ek, Ieva Kazlauskaite
Optimisation of a global climate model ensemble for prediction of extreme heat days. CoRR (2022)
Arnaud Vadeboncoeur, Ömer Deniz Akyildiz, Ieva Kazlauskaite, Mark Girolami, Fehmi Cirak
Deep Probabilistic Models for Forward and Inverse Problems in Parametric PDEs. CoRR (2022)
Aditya Ravuri, Tom R. Andersson, Ieva Kazlauskaite, Will Tebbutt, Richard E. Turner, J. Scott Hosking, Neil D. Lawrence, Markus Kaiser
Ice Core Dating using Probabilistic Programming. CoRR (2022)
Olga Mikheeva, Ieva Kazlauskaite, Adam Hartshorne, Hedvig Kjellström, Carl Henrik Ek, Neill D. F. Campbell
Aligned Multi-Task Gaussian Process. AISTATS (2022)
Olga Mikheeva, Ieva Kazlauskaite, Adam Hartshorne, Hedvig Kjellström, Carl Henrik Ek, Neill D. F. Campbell
Aligned Multi-Task Gaussian Process. CoRR (2021)
Erik Bodin, Markus Kaiser, Ieva Kazlauskaite, Zhenwen Dai, Neill W. Campbell, Carl Henrik Ek
Modulating Surrogates for Bayesian Optimization. ICML (2020)
Olga Mikheeva, Ieva Kazlauskaite, Hedvig Kjellström, Carl Henrik Ek
Bayesian nonparametric shared multi-sequence time series segmentation. CoRR (2020)
Ivan Ustyuzhaninov, Ieva Kazlauskaite, Carl Henrik Ek, Neill D. F. Campbell
Monotonic Gaussian Process Flows. AISTATS (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)
Ieva Kazlauskaite, Carl Henrik Ek, Neill D. F. Campbell
Gaussian Process Latent Variable Alignment Learning. AISTATS (2019)
Ivan Ustyuzhaninov, Ieva Kazlauskaite, Carl Henrik Ek, Neill D. F. Campbell
Monotonic Gaussian Process Flow. CoRR (2019)
Ieva Kazlauskaite, Ivan Ustyuzhaninov, Carl Henrik Ek, Neill D. F. Campbell
Sequence Alignment with Dirichlet Process Mixtures. CoRR (2018)
Ieva Kazlauskaite, Carl Henrik Ek, Neill D. F. Campbell
Gaussian Process Latent Variable Alignment Learning. CoRR (2018)