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2020 – today
- 2026
[i18]Theo X. Olausson, Metod Jazbec, Xi Wang, Armando Solar-Lezama, Christian A. Naesseth, Stephan Mandt, Eric T. Nalisnick:
A Tale of Two Temperatures: Simple, Efficient, and Diverse Sampling from Diffusion Language Models. CoRR abs/2604.09921 (2026)- [i17]Ha Manh Bui, Metod Jazbec, Eric T. Nalisnick, Anqi Liu:
Efficient and Uncertainty-Aware Diffusion Framework for Offline-to-Online Reinforcement Learning. CoRR abs/2605.30776 (2026) - [i16]Stipe Frkovic, Metod Jazbec, Dan Zhang, Christian A. Naesseth, Ilija Bogunovic, Eric T. Nalisnick:
Re-evaluating Confidence Remasking in Masked Diffusion Language Models. CoRR abs/2606.12232 (2026) - [i15]Paul Seij, Christian A. Naesseth, Stephan Mandt, Metod Jazbec:
Uncertainty Estimation for Molecular Diffusion Models. CoRR abs/2606.13451 (2026) - 2025
- [c6]Mona Schirmer, Metod Jazbec, Christian Andersson Naesseth, Eric T. Nalisnick:
Monitoring Risks in Test-Time Adaptation. NeurIPS 2025 - [c5]Metod Jazbec, Eliot Wong-Toi, Guoxuan Xia, Dan Zhang, Eric T. Nalisnick, Stephan Mandt:
Generative Uncertainty in Diffusion Models. UAI 2025: 1837-1858 - [i14]Metod Jazbec, Eliot Wong-Toi, Guoxuan Xia, Dan Zhang, Eric T. Nalisnick, Stephan Mandt:
Generative Uncertainty in Diffusion Models. CoRR abs/2502.20946 (2025) - [i13]Mona Schirmer, Metod Jazbec, Christian A. Naesseth, Eric T. Nalisnick:
Monitoring Risks in Test-Time Adaptation. CoRR abs/2507.08721 (2025) - [i12]Piotr Kubaty, Filip Szatkowski, Metod Jazbec, Bartosz Wójcik:
Failure Prediction Is a Better Performance Proxy for Early-Exit Networks Than Calibration. CoRR abs/2508.21495 (2025) - [i11]Andrea Wynn, Metod Jazbec, Charith Peris, Rinat Khaziev, Anqi Liu, Daniel Khashabi, Eric T. Nalisnick:
Safe and Efficient In-Context Learning via Risk Control. CoRR abs/2510.02480 (2025) - [i10]Jort Vincenti, Metod Jazbec, Guoxuan Xia:
Dynamic Mixture-of-Experts for Visual Autoregressive Model. CoRR abs/2510.08629 (2025) - [i9]Metod Jazbec, Theo X. Olausson, Louis Béthune, Pierre Ablin, Michael Kirchhof, João Monteiro, Victor Turrisi, Jason Ramapuram, Marco Cuturi:
Learning Unmasking Policies for Diffusion Language Models. CoRR abs/2512.09106 (2025) - 2024
- [c4]Metod Jazbec, Alexander Timans, Tin Hadzi Veljkovic, Kaspar Sakmann, Dan Zhang, Christian Andersson Naesseth, Eric T. Nalisnick:
Fast yet Safe: Early-Exiting with Risk Control. NeurIPS 2024 - [c3]Metod Jazbec, Patrick Forré, Stephan Mandt, Dan Zhang, Eric T. Nalisnick:
Early-Exit Neural Networks with Nested Prediction Sets. UAI 2024: 1780-1796 - [i8]Metod Jazbec, Alexander Timans, Tin Hadzi Veljkovic, Kaspar Sakmann, Dan Zhang, Christian A. Naesseth, Eric T. Nalisnick:
Fast yet Safe: Early-Exiting with Risk Control. CoRR abs/2405.20915 (2024) - [i7]Daniel Gallo Fernández, Razvan-Andrei Matisan, Alejandro Monroy Muñoz, Ana-Maria Vasilcoiu, Janusz Partyka, Tin Hadzi Veljkovic, Metod Jazbec:
DuoDiff: Accelerating Diffusion Models with a Dual-Backbone Approach. CoRR abs/2410.09633 (2024) - [i6]Jort Vincenti, Karim Abdel Sadek
, Joan Velja, Matteo Nulli, Metod Jazbec:
Dynamic Vocabulary Pruning in Early-Exit LLMs. CoRR abs/2410.18952 (2024) - 2023
- [c2]Metod Jazbec, James Urquhart Allingham, Dan Zhang, Eric T. Nalisnick:
Towards Anytime Classification in Early-Exit Architectures by Enforcing Conditional Monotonicity. NeurIPS 2023 - [i5]Metod Jazbec, James Urquhart Allingham, Dan Zhang, Eric T. Nalisnick:
Towards Anytime Classification in Early-Exit Architectures by Enforcing Conditional Monotonicity. CoRR abs/2306.02652 (2023) - [i4]Metod Jazbec, Patrick Forré, Stephan Mandt, Dan Zhang, Eric T. Nalisnick:
Anytime-Valid Confidence Sequences for Consistent Uncertainty Estimation in Early-Exit Neural Networks. CoRR abs/2311.05931 (2023) - 2021
- [c1]Metod Jazbec, Matthew Ashman, Vincent Fortuin, Michael Pearce, Stephan Mandt, Gunnar Rätsch:
Scalable Gaussian Process Variational Autoencoders. AISTATS 2021: 3511-3519 - 2020
- [i3]Metod Jazbec, Barna Pásztor, Felix Faltings, Nino Antulov-Fantulin, Petter N. Kolm:
On the impact of publicly available news and information transfer to financial markets. CoRR abs/2010.12002 (2020) - [i2]Metod Jazbec, Vincent Fortuin, Michael Pearce, Stephan Mandt, Gunnar Rätsch:
Scalable Gaussian Process Variational Autoencoders. CoRR abs/2010.13472 (2020) - [i1]Metod Jazbec, Michael Pearce, Vincent Fortuin:
Factorized Gaussian Process Variational Autoencoders. CoRR abs/2011.07255 (2020)
Coauthor Index
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