Peharz, Robert

33 publications

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

TMLR 2025 What Is the Relationship Between Tensor Factorizations and Circuits (and How Can We Exploit It)? Lorenzo Loconte, Antonio Mari, Gennaro Gala, Robert Peharz, Cassio de Campos, Erik Quaeghebeur, Gennaro Vessio, Antonio Vergari

ICMLW 2024 Bayesian Optimization for the Discovery of Redox Active Quinones Giacomo De Gobbi, Reyhan Yagmur, Janine Maier, Stefan Spirk, Robert Peharz

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

ICML 2024 Exact Soft Analytical Side-Channel Attacks Using Tractable Circuits Thomas Wedenig, Rishub Nagpal, Gaëtan Cassiers, Stefan Mangard, Robert Peharz

ICMLW 2024 Exact Soft Analytical Side-Channel Attacks Using Tractable Circuits Thomas Wedenig, Rishub Nagpal, Gaëtan Cassiers, Stefan Mangard, Robert Peharz

AISTATS 2024 Probabilistic Integral Circuits Gennaro Gala, Cassio Campos, Robert Peharz, Antonio Vergari, Erik Quaeghebeur

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

AISTATS 2023 Bayesian Structure Scores for Probabilistic Circuits Yang Yang, Gennaro Gala, Robert Peharz

AAAI 2023 Continuous Mixtures of Tractable Probabilistic Models Alvaro H. C. Correia, Gennaro Gala, Erik Quaeghebeur, Cassio P. de Campos, Robert Peharz

NeurIPS 2023 How to Turn Your Knowledge Graph Embeddings into Generative Models Lorenzo Loconte, Nicola Di Mauro, Robert Peharz, Antonio Vergari

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

PGM 2020 Conditional Sum-Product Networks: Imposing Structure on Deep Probabilistic Architectures Xiaoting Shao, Alejandro Molina, Antonio Vergari, Karl Stelzner, Robert Peharz, Thomas Liebig, Kristian Kersting

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

ICML 2020 Einsum Networks: Fast and Scalable Learning of Tractable Probabilistic Circuits Robert Peharz, Steven Lang, Antonio Vergari, Karl Stelzner, Alejandro Molina, Martin Trapp, Guy Van Den Broeck, Kristian Kersting, Zoubin Ghahramani

NeurIPS 2020 Joints in Random Forests Alvaro Correia, Robert Peharz, Cassio P de Campos

ECML-PKDD 2020 PS3: Partition-Based Skew-Specialized Sampling for Batch Mode Active Learning in Imbalanced Text Data Ricky Maulana Fajri, Samaneh Khoshrou, Robert Peharz, Mykola Pechenizkiy

PGM 2020 Sum-Product Network Decompilation Cory Butz, Jhonatan S. Oliveira, Robert Peharz

AAAI 2019 Automatic Bayesian Density Analysis Antonio Vergari, Alejandro Molina, Robert Peharz, Zoubin Ghahramani, Kristian Kersting, Isabel Valera

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

ICML 2019 Faster Attend-Infer-Repeat with Tractable Probabilistic Models Karl Stelzner, Robert Peharz, Kristian Kersting

ICML 2019 Hierarchical Decompositional Mixtures of Variational Autoencoders Ping Liang Tan, Robert Peharz

ICLR 2019 Minimal Random Code Learning: Getting Bits Back from Compressed Model Parameters Marton Havasi, Robert Peharz, José Miguel Hernández-Lobato

UAI 2019 Random Sum-Product Networks: A Simple and Effective Approach to Probabilistic Deep Learning Robert Peharz, Antonio Vergari, Karl Stelzner, Alejandro Molina, Xiaoting Shao, Martin Trapp, Kristian Kersting, Zoubin Ghahramani

AAAI 2018 Sum-Product Autoencoding: Encoding and Decoding Representations Using Sum-Product Networks Antonio Vergari, Robert Peharz, Nicola Di Mauro, Alejandro Molina, Kristian Kersting, Floriana Esposito

ICLR 2017 Encoding and Decoding Representations with Sum- and Max-Product Networks Antonio Vergari, Robert Peharz, Nicola Di Mauro, Floriana Esposito

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

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

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

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

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