Bálint Mucsányi

19 papers A* 3C 1Journal 14Unranked 1
YearRankTypeTitle / Venue / Authors
2026 J jnl
Dynamics Reveals Structure: Challenging the Linear Propagation Assumption.
CoRR
Hoyeon Chang, Bálint Mucsányi, Seong Joon Oh
2025 A* conf
Debiasing Mini-Batch Quadratics for Applications in Deep Learning.
ICLR
Lukas Tatzel, Bálint Mucsányi, Osane Hackel, Philipp Hennig
2025 — conf
Geometric Gaussian Approximations of Probability Distributions.
GSI (3)
Nathaël Da Costa, Bálint Mucsányi, Philipp Hennig
2025 J jnl
Geometric Gaussian Approximations of Probability Distributions.
CoRR
Nathaël Da Costa, Bálint Mucsányi, Philipp Hennig
2025 J jnl
Kronecker-factored Approximate Curvature (KFAC) From Scratch.
CoRR
Felix Dangel, Bálint Mucsányi, Tobias Weber, Runa Eschenhagen
2025 J jnl
Logit Reweighting for Topic-Focused Summarization.
CoRR
Joschka Braun, Bálint Mucsányi, Seyed Ali Bahrainian
2025 J jnl
Rethinking Approximate Gaussian Inference in Classification.
CoRR
Bálint Mucsányi, Nathaël Da Costa, Philipp Hennig
2025 J jnl
Skill Learning via Policy Diversity Yields Identifiable Representations for Reinforcement Learning.
CoRR
Patrik Reizinger, Bálint Mucsányi, Siyuan Guo, Benjamin Eysenbach, Bernhard Schölkopf, Wieland Brendel
2025 J jnl
laplax - Laplace Approximations with JAX.
CoRR
Tobias Weber, Bálint Mucsányi, Lenard Rommel, Thomas Christie, Lars Kasüschke, Marvin Pförtner, Philipp Hennig
2025 J jnl
sbi reloaded: a toolkit for simulation-based inference workflows.
J. Open Source Softw.
Jan Boelts, Michael Deistler, Manuel Glöckler, Álvaro Tejero-Cantero, Jan-Matthis Lueckmann, Guy Moss, Peter Steinbach, Thomas Moreau, Fabio Muratore, Julia Linhart, Conor Durkan, Julius Vetter, Benjamin Kurt Miller, Maternus Herold, Abolfazl Ziaeemehr, Matthijs Pals, Theo Gruner, Sebastian Bischoff, Nastya Krouglova, Richard Gao, Janne K. Lappalainen, Bálint Mucsányi, Felix Pei, Auguste Schulz, Zinovia Stefanidi, Pedro Rodrigues, Cornelius Schröder, Faried Abu Zaid, Jonas Beck, Jaivardhan Kapoor, David S. Greenberg, Pedro J. Gonçalves, Jakob H. Macke
2024 A* conf
Benchmarking Uncertainty Disentanglement: Specialized Uncertainties for Specialized Tasks.
NeurIPS
Bálint Mucsányi, Michael Kirchhof, Seong Joon Oh
2024 J jnl
Benchmarking Uncertainty Disentanglement: Specialized Uncertainties for Specialized Tasks.
CoRR
Bálint Mucsányi, Michael Kirchhof, Seong Joon Oh
2024 J jnl
Debiasing Mini-Batch Quadratics for Applications in Deep Learning.
CoRR
Lukas Tatzel, Bálint Mucsányi, Osane Hackel, Philipp Hennig
2024 J jnl
sbi reloaded: a toolkit for simulation-based inference workflows.
CoRR
Jan Boelts, Michael Deistler, Manuel Glöckler, Álvaro Tejero-Cantero, Jan-Matthis Lueckmann, Guy Moss, Peter Steinbach, Thomas Moreau, Fabio Muratore, Julia Linhart, Conor Durkan, Julius Vetter, Benjamin Kurt Miller, Maternus Herold, Abolfazl Ziaeemehr, Matthijs Pals, Theo Gruner, Sebastian Bischoff, Nastya Krouglova, Richard Gao, Janne K. Lappalainen, Bálint Mucsányi, Felix Pei, Auguste Schulz, Zinovia Stefanidi, Pedro Rodrigues, Cornelius Schröder, Faried Abu Zaid, Jonas Beck, Jaivardhan Kapoor, David S. Greenberg, Pedro J. Gonçalves, Jakob H. Macke
2023 J jnl
Trustworthy Machine Learning.
CoRR
Bálint Mucsányi, Michael Kirchhof, Elisa Nguyen, Alexander Rubinstein, Seong Joon Oh
2023 A* conf
URL: A Representation Learning Benchmark for Transferable Uncertainty Estimates.
NeurIPS
Michael Kirchhof, Bálint Mucsányi, Seong Joon Oh, Enkelejda Kasneci
2023 J jnl
URL: A Representation Learning Benchmark for Transferable Uncertainty Estimates.
CoRR
Michael Kirchhof, Bálint Mucsányi, Seong Joon Oh, Enkelejda Kasneci
2022 J jnl
Flexible Example-Based Program Synthesis on Tree-Structured Function Compositions.
SN Comput. Sci.
Bálint Mucsányi, Bálint Gyarmathy, Ádám Czapp, Balázs Pintér
2021 C conf
Flexcoder: Practical Program Synthesis with Flexible Input Lengths and Expressive Lambda Functions.
ICPRAM
Bálint Gyarmathy, Bálint Mucsányi, Ádám Czapp, Dávid Szilágyi, Balázs Pintér