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Ieva Kazlauskaite
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2020 – today
- 2024
- [i13]Thomas A. Archbold, Ieva Kazlauskaite, Fehmi Cirak:
Variational Bayesian surrogate modelling with application to robust design optimisation. CoRR abs/2404.14857 (2024) - [i12]Alex Glyn-Davies, Arnaud Vadeboncoeur, Ömer Deniz Akyildiz, Ieva Kazlauskaite, Mark Girolami:
A Primer on Variational Inference for Physics-Informed Deep Generative Modelling. CoRR abs/2409.06560 (2024) - 2023
- [j1]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: 112369 (2023) - [c6]Arnaud Vadeboncoeur, Ieva Kazlauskaite, Yanni Papandreou, Fehmi Cirak, Mark Girolami, Ömer Deniz Akyildiz:
Random Grid Neural Processes for Parametric Partial Differential Equations. ICML 2023: 34759-34778 - [i11]Arnaud Vadeboncoeur, Ieva Kazlauskaite, Yanni Papandreou, Fehmi Cirak, Mark Girolami, Ömer Deniz Akyildiz:
Random Grid Neural Processes for Parametric Partial Differential Equations. CoRR abs/2301.11040 (2023) - 2022
- [c5]Olga Mikheeva, Ieva Kazlauskaite, Adam Hartshorne, Hedvig Kjellström, Carl Henrik Ek, Neill D. F. Campbell:
Aligned Multi-Task Gaussian Process. AISTATS 2022: 2970-2988 - [i10]Arnaud Vadeboncoeur, Ömer Deniz Akyildiz, Ieva Kazlauskaite, Mark Girolami, Fehmi Cirak:
Deep Probabilistic Models for Forward and Inverse Problems in Parametric PDEs. CoRR abs/2208.04856 (2022) - [i9]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 abs/2210.16568 (2022) - [i8]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 abs/2211.16367 (2022) - 2021
- [i7]Olga Mikheeva, Ieva Kazlauskaite, Adam Hartshorne, Hedvig Kjellström, Carl Henrik Ek, Neill D. F. Campbell:
Aligned Multi-Task Gaussian Process. CoRR abs/2110.15761 (2021) - 2020
- [b1]Ieva Kazlauskaite:
Compositional uncertainty in models of alignment. University of Bath, UK, 2020 - [c4]Ivan Ustyuzhaninov, Ieva Kazlauskaite, Carl Henrik Ek, Neill D. F. Campbell:
Monotonic Gaussian Process Flows. AISTATS 2020: 3057-3067 - [c3]Erik Bodin, Markus Kaiser, Ieva Kazlauskaite, Zhenwen Dai, Neill W. Campbell, Carl Henrik Ek:
Modulating Surrogates for Bayesian Optimization. ICML 2020: 970-979 - [c2]Ivan Ustyuzhaninov, Ieva Kazlauskaite, Markus Kaiser, Erik Bodin, Neill D. F. Campbell, Carl Henrik Ek:
Compositional uncertainty in deep Gaussian processes. UAI 2020: 480-489 - [i6]Olga Mikheeva, Ieva Kazlauskaite, Hedvig Kjellström, Carl Henrik Ek:
Bayesian nonparametric shared multi-sequence time series segmentation. CoRR abs/2001.09886 (2020)
2010 – 2019
- 2019
- [c1]Ieva Kazlauskaite, Carl Henrik Ek, Neill D. F. Campbell:
Gaussian Process Latent Variable Alignment Learning. AISTATS 2019: 748-757 - [i5]Ivan Ustyuzhaninov, Ieva Kazlauskaite, Carl Henrik Ek, Neill D. F. Campbell:
Monotonic Gaussian Process Flow. CoRR abs/1905.12930 (2019) - [i4]Erik Bodin, Markus Kaiser, Ieva Kazlauskaite, Neill D. F. Campbell, Carl Henrik Ek:
Modulated Bayesian Optimization using Latent Gaussian Process Models. CoRR abs/1906.11152 (2019) - [i3]Ivan Ustyuzhaninov, Ieva Kazlauskaite, Markus Kaiser, Erik Bodin, Neill D. F. Campbell, Carl Henrik Ek:
Compositional uncertainty in deep Gaussian processes. CoRR abs/1909.07698 (2019) - 2018
- [i2]Ieva Kazlauskaite, Carl Henrik Ek, Neill D. F. Campbell:
Gaussian Process Latent Variable Alignment Learning. CoRR abs/1803.02603 (2018) - [i1]Ieva Kazlauskaite, Ivan Ustyuzhaninov, Carl Henrik Ek, Neill D. F. Campbell:
Sequence Alignment with Dirichlet Process Mixtures. CoRR abs/1811.10689 (2018)
Coauthor Index
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last updated on 2024-10-22 20:17 CEST by the dblp team
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