Metod Jazbec

Cited by

	All	Since 2020
Citations	63	63
h-index	4	4
i10-index	2	2

2020202120222023202420251 11 8 13 25 5

Public access

View all

2 articles

0 articles

available

not available

Based on funding mandates

Co-authors

Stephan MandtAssociate Professor, University of California, IrvineVerified email at uci.edu
Eric NalisnickAssistant Professor, Johns Hopkins UniversityVerified email at jhu.edu
Dan ZhangSenior Expert at Bosch Center for Artificial Intelligence, Robert Bosch GmbHVerified email at bosch.com
Vincent FortuinPrincipal Investigator, Helmholtz AI & TU MunichVerified email at tum.de
Michael PearceSenior Researcher, BelfastVerified email at warwick.ac.uk
Gunnar RätschProfessor, ETH ZürichVerified email at inf.ethz.ch
Matthew AshmanPhD Student, University of CambridgeVerified email at cam.ac.uk
Tin Hadži VeljkovićUniversity of AmsterdamVerified email at uva.nl
James Urquhart AllinghamGoogle DeepMindVerified email at cam.ac.uk
Petter KolmNYU Courant Institute of Mathematical SciencesVerified email at nyu.edu
Nino Antulov-FantulinHead of Research @ Aisot Technologies, Privatdozent at ETH ZurichVerified email at ethz.ch
Barna PásztorETH AI CenterVerified email at ethz.ch
Felix FaltingsPhD student, MITVerified email at mit.edu
Patrick ForréAssociate Professor Machine Learning, AI4Science Lab Manager, University of AmsterdamVerified email at uva.nl
Alexander TimansUniversity of AmsterdamVerified email at uva.nl
Christian A. NaessethAssistant Professor, University of AmsterdamVerified email at uva.nl
Menglin XiaMicrosoftVerified email at microsoft.com
Guoxuan XiaImperial College LondonVerified email at imperial.ac.uk
Eliot Wong-ToiUniversity of California, IrvineVerified email at uci.edu

Metod Jazbec

University of Amsterdam

Verified email at uva.nl - Homepage

Machine Learning


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
Scalable gaussian process variational autoencoders M Jazbec, M Ashman, V Fortuin, M Pearce, S Mandt, G Rätsch International Conference on Artificial Intelligence and Statistics, 3511-3519, 2021	31	2021
Towards anytime classification in early-exit architectures by enforcing conditional monotonicity M Jazbec, J Allingham, D Zhang, E Nalisnick Advances in Neural Information Processing Systems 36, 2024	12	2024
Factorized Gaussian Process Variational Autoencoders M Jazbec, M Pearce, V Fortuin Symposium on Advances in Approximate Bayesian Inference (AABI), 2020	9	2020
On the impact of publicly available news and information transfer to financial markets M Jazbec, B Pàsztor, F Faltings, N Antulov-Fantulin, PN Kolm Royal Society Open Science 8 (7), 202321, 2021	6	2021
Fast yet safe: Early-exiting with risk control M Jazbec, A Timans, T Hadži Veljković, K Sakmann, D Zhang, ... Advances in Neural Information Processing Systems 37, 129825-129854, 2024	4	2024
Early-Exit Neural Networks with Nested Prediction Sets M Jazbec, P Forré, S Mandt, D Zhang, E Nalisnick The 40th Conference on Uncertainty in Artificial Intelligence, 2024	1*	2024
Generative Uncertainty in Diffusion Models M Jazbec, E Wong-Toi, G Xia, D Zhang, E Nalisnick, S Mandt arXiv preprint arXiv:2502.20946, 2025		2025
Dynamic Vocabulary Pruning in Early-Exit LLMs J Vincenti, KA Sadek, J Velja, M Nulli, M Jazbec arXiv preprint arXiv:2410.18952, 2024		2024
DuoDiff: Accelerating Diffusion Models with a Dual-Backbone Approach DG Fernández, RA Matişan, AM Muñoz, AM Vasilcoiu, J Partyka, ... arXiv preprint arXiv:2410.09633, 2024		2024
On Efficient Distillation from LLMs to SLMs M Jazbec, M Xia, A Mallick, D Madrigal, D Han, S Kessler, V Rühle NeurIPS 2024 Workshop on Fine-Tuning in Modern Machine Learning: Principles …, 0

The system can't perform the operation now. Try again later.

Articles 1–10

Citations per year

Duplicate citations

Merged citations

Add co-authorsCo-authors

Follow

Cited by

Co-authors