Pernkopf, Franz

39 publications

AISTATS 2025 Effective Bayesian Causal Inference via Structural Marginalisation and Autoregressive Orders Christian Toth, Christian Knoll, Franz Pernkopf, Robert Peharz

ICMLW 2024 Effective Bayesian Causal Inference via Structural Marginalisation and Autoregressive Orders Christian Toth, Christian Knoll, Franz Pernkopf, Robert Peharz

ICMLW 2024 Function Space Diversity for Uncertainty Prediction via Repulsive Last-Layer Ensembles Sophie Steger, Christian Knoll, Bernhard Klein, Holger Fröning, Franz Pernkopf

ICLRW 2024 On Training Physics-Informed Neural Networks for Oscillating Problems Martin Hofmann-Wellenhof, Alexander Fuchs, Franz Pernkopf

ICMLW 2024 Reliability Thresholds for the Bethe Free Energy Approximation Harald Leisenberger, Christian Knoll, Franz Pernkopf

JMLR 2024 Resource-Efficient Neural Networks for Embedded Systems Wolfgang Roth, Günther Schindler, Bernhard Klein, Robert Peharz, Sebastian Tschiatschek, Holger Fröning, Franz Pernkopf, Zoubin Ghahramani

ICMLW 2024 Robustness of Explainable Artificial Intelligence in Industrial Process Modelling Benedikt Kantz, Clemens Staudinger, Christoph Feilmayr, Johannes Wachlmayr, Alexander Haberl, Stefan Schuster, Franz Pernkopf

ICMLW 2024 Two-Level Test-Time Adaptation in Multimodal Learning Jixiang Lei, Franz Pernkopf

NeurIPS 2022 Active Bayesian Causal Inference Christian Toth, Lars Lorch, Christian Knoll, Andreas Krause, Franz Pernkopf, Robert Peharz, Julius von Kügelgen

NeurIPSW 2022 Active Bayesian Causal Inference Christian Toth, Lars Lorch, Christian Knoll, Andreas Krause, Franz Pernkopf, Robert Peharz, Julius Von Kügelgen

NeurIPSW 2022 Active Bayesian Causal Inference Christian Toth, Lars Lorch, Christian Knoll, Andreas Krause, Franz Pernkopf, Robert Peharz, Julius Von Kügelgen

ACML 2022 Example or Prototype? Learning Concept-Based Explanations in Time-Series Christoph Obermair, Alexander Fuchs, Franz Pernkopf, Lukas Felsberger, Andrea Apollonio, Daniel Wollmann

UAI 2022 Fixing the Bethe Approximation: How Structural Modifications in a Graph Improve Belief Propagation Harald Leisenberger, Franz Pernkopf, Christian Knoll

UAI 2021 Convergence Behavior of Belief Propagation: Estimating Regions of Attraction via Lyapunov Functions Harald Leisenberger, Christian Knoll, Richard Seeber, Franz Pernkopf

NeurIPSW 2021 Distribution Mismatch Correction for Improved Robustness in Deep Neural Networks Alexander Fuchs, Christian Knoll, Franz Pernkopf

AISTATS 2020 Deep Structured Mixtures of Gaussian Processes Martin Trapp, Robert Peharz, Franz Pernkopf, Carl Edward Rasmussen

PGM 2020 Differentiable TAN Structure Learning for Bayesian Network Classifiers Wolfgang Roth, Franz Pernkopf

NeurIPS 2019 Bayesian Learning of Sum-Product Networks Martin Trapp, Robert Peharz, Hong Ge, Franz Pernkopf, Zoubin Ghahramani

UAI 2019 Belief Propagation: Accurate Marginals or Accurate Partition Function – Where Is the Difference? Christian Knoll, Franz Pernkopf

ECML-PKDD 2019 Training Discrete-Valued Neural Networks with Sign Activations Using Weight Distributions Wolfgang Roth, Günther Schindler, Holger Fröning, Franz Pernkopf

ECML-PKDD 2018 Towards Efficient Forward Propagation on Resource-Constrained Systems Günther Schindler, Matthias Zöhrer, Franz Pernkopf, Holger Fröning

UAI 2017 On Loopy Belief Propagation - Local Stability Analysis for Non-Vanishing Fields Christian Knoll, Franz Pernkopf

UAI 2017 Safe Semi-Supervised Learning of Sum-Product Networks Martin Trapp, Tamas Madl, Robert Peharz, Franz Pernkopf, Robert Trappl

ECML-PKDD 2015 Message Scheduling Methods for Belief Propagation Christian Knoll, Michael Rath, Sebastian Tschiatschek, Franz Pernkopf

AISTATS 2015 On Theoretical Properties of Sum-Product Networks Robert Peharz, Sebastian Tschiatschek, Franz Pernkopf, Pedro M. Domingos

ECML-PKDD 2015 Parameter Learning of Bayesian Network Classifiers Under Computational Constraints Sebastian Tschiatschek, Franz Pernkopf

ECML-PKDD 2015 Structured Regularizer for Neural Higher-Order Sequence Models Martin Ratajczak, Sebastian Tschiatschek, Franz Pernkopf

NeurIPS 2014 General Stochastic Networks for Classification Matthias Zöhrer, Franz Pernkopf

ECML-PKDD 2014 Integer Bayesian Network Classifiers Sebastian Tschiatschek, Karin Paul, Franz Pernkopf

ECML-PKDD 2013 Greedy Part-Wise Learning of Sum-Product Networks Robert Peharz, Bernhard C. Geiger, Franz Pernkopf

AISTATS 2013 On the Asymptotic Optimality of Maximum Margin Bayesian Networks Sebastian Tschiatschek, Franz Pernkopf

ICML 2013 The Most Generative Maximum Margin Bayesian Networks Robert Peharz, Sebastian Tschiatschek, Franz Pernkopf

ECML-PKDD 2012 Bayesian Network Classifiers with Reduced Precision Parameters Sebastian Tschiatschek, Peter Reinprecht, Manfred Mücke, Franz Pernkopf

ICML 2012 Exact Maximum Margin Structure Learning of Bayesian Networks Robert Peharz, Franz Pernkopf

JMLR 2010 Efficient Heuristics for Discriminative Structure Learning of Bayesian Network Classifiers Franz Pernkopf, Jeff A. Bilmes

ECML-PKDD 2010 Large Margin Learning of Bayesian Classifiers Based on Gaussian Mixture Models Franz Pernkopf, Michael Wohlmayr

ECML-PKDD 2009 On Discriminative Parameter Learning of Bayesian Network Classifiers Franz Pernkopf, Michael Wohlmayr

ICML 2005 Discriminative Versus Generative Parameter and Structure Learning of Bayesian Network Classifiers Franz Pernkopf, Jeff A. Bilmes

AAAI 2004 Bayesian Network Classifiers Versus k-NN Classifier Using Sequential Feature Selection Franz Pernkopf