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Ieva Kazlauskaite
Ieva Kazlauskaite
London School of Economics and Political Science
Bestätigte E-Mail-Adresse bei lse.ac.uk
Titel
Zitiert von
Zitiert von
Jahr
Gaussian Process Latent Variable Alignment Learning
I Kazlauskaite, CH Ek, NDF Campbell
International Conference on Artificial Intelligence and Statistics (AISTATS …, 2019
252019
Monotonic Gaussian Process Flow
I Ustyuzhaninov, I Kazlauskaite, CH Ek, NDF Campbell
International Conference on Artificial Intelligence and Statistics (AISTATS …, 2020
242020
Compositional uncertainty in deep Gaussian processes
I Ustyuzhaninov, I Kazlauskaite, M Kaiser, E Bodin, N Campbell, CH Ek
Conference on Uncertainty in Artificial Intelligence, 480-489, 2020
232020
Variational Bayesian approximation of inverse problems using sparse precision matrices
J Povala, I Kazlauskaite, E Febrianto, F Cirak, M Girolami
Computer Methods in Applied Mechanics and Engineering 393, 114712, 2022
212022
Fully probabilistic deep models for forward and inverse problems in parametric PDEs
A Vadeboncoeur, ÖD Akyildiz, I Kazlauskaite, M Girolami, F Cirak
Journal of Computational Physics 491, 112369, 2023
172023
Modulating Surrogates for Bayesian Optimization
E Bodin, M Kaiser, I Kazlauskaite, Z Dai, NDF Campbell, CH Ek
International Conference on Machine Learning (ICML 2020), arXiv: 1906.11152, 2019
162019
Random Grid Neural Processes for Parametric Partial Differential Equations
A Vadeboncoeur, I Kazlauskaite, Y Papandreou, F Cirak, M Girolami, ...
International Conference on Machine Learning, 34759-34778, 2023
102023
Multi-fidelity experimental design for ice-sheet simulation
P Thodoroff, M Kaiser, R Williams, R Arthern, S Hosking, N Lawrence, ...
NeurIPS Workshop on Gaussian Processes, Spatiotemporal Modeling, and …, 2022
52022
Calculating exposure to extreme sea level risk will require high resolution ice sheet models
C Williams, P Thodoroff, R Arthern, J Byrne, JS Hosking, M Kaiser, ...
22023
Aligned Multi-Task Gaussian Process
O Mikheeva, I Kazlauskaite, A Hartshorne, H Kjellström, CH Ek, ...
International Conference on Artificial Intelligence and Statistics, 2970-2988, 2022
22022
The Bayesian approach to inverse robin problems
AK Rasmussen, F Seizilles, M Girolami, I Kazlauskaite
SIAM/ASA Journal on Uncertainty Quantification 12 (3), 1050-1084, 2024
12024
Variational Bayesian surrogate modelling with application to robust design optimisation
TA Archbold, I Kazlauskaite, F Cirak
arXiv preprint arXiv:2404.14857, 2024
12024
Sequence Alignment with Dirichlet Process Mixtures
I Kazlauskaite, I Ustyuzhaninov, CH Ek, NDF Campbell
NeurIPS, Workshop on Bayesian Nonparametrics (BNP@NeurIPS), 2018, 2018
12018
Statistical Finite Elements via Interacting Particle Langevin Dynamics
A Glyn-Davies, C Duffin, I Kazlauskaite, M Girolami, ÖD Akyildiz
arXiv preprint arXiv:2409.07101, 2024
2024
A Primer on Variational Inference for Physics-Informed Deep Generative Modelling
A Glyn-Davies, A Vadeboncoeur, OD Akyildiz, I Kazlauskaite, M Girolami
arXiv preprint arXiv:2409.06560, 2024
2024
Limits to the predictability of extreme heat events
M Virdee, E Shuckburgh, I Kazlauskaite, E Boland, A Ming
AGU Fall Meeting Abstracts 2023, GC33A-03, 2023
2023
A locally time-invariant metric for climate model ensemble predictions of extreme risk
M Virdee, M Kaiser, CH Ek, E Shuckburgh, I Kazlauskaite
Environmental Data Science 2, E26, 2023
2023
Probabilistic Machine Learning for Automated Ice Core Dating
A Ravuri, T Andersson, M Kaiser, I Kazlauskaite, M Fryer, JS Hosking, ...
AGU Fall Meeting 2022, 2022
2022
Ice Core Dating using Probabilistic Programming
A Ravuri, TR Andersson, I Kazlauskaite, W Tebbutt, RE Turner, ...
arXiv preprint arXiv:2210.16568, 2022
2022
Bayesian nonparametric shared multi-sequence time series segmentation
O Mikheeva, I Kazlauskaite, H Kjellström, CH Ek
arXiv preprint arXiv:2001.09886, 2020
2020
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