Robert Peharz - RankMe

68 papers A* 12A 10Misc 4Journal 34Unranked 8

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	Deep Polynomial Chaos Expansion. CoRR Johannes Exenberger, Sascha Ranftl, Robert Peharz
2025	A	`conf`	Effective Bayesian Causal Inference via Structural Marginalisation and Autoregressive Orders. AISTATS Christian Toth, Christian Knoll, Franz Pernkopf, Robert Peharz
2025	J	`jnl`	Exact Soft Analytical Side-Channel Attacks using Tractable Circuits. CoRR Thomas Wedenig, Rishub Nagpal, Gaëtan Cassiers, Stefan Mangard, Robert Peharz
2025	J	`jnl`	What is the Relationship between Tensor Factorizations and Circuits (and How Can We Exploit it)? Trans. Mach. Learn. Res. Lorenzo Loconte, Antonio Mari, Gennaro Gala, Robert Peharz, Cassio de Campos, Erik Quaeghebeur, Gennaro Vessio, Antonio Vergari
2024	A*	`conf`	Exact Soft Analytical Side-Channel Attacks using Tractable Circuits. ICML Thomas Wedenig, Rishub Nagpal, Gaëtan Cassiers, Stefan Mangard, Robert Peharz
2024	J	`jnl`	One-Shot Federated Learning with Bayesian Pseudocoresets. CoRR Tim D'Hondt, Mykola Pechenizkiy, Robert Peharz
2024	A	`conf`	Probabilistic Integral Circuits. AISTATS Gennaro Gala, Cassio P. de Campos, Robert Peharz, Antonio Vergari, Erik Quaeghebeur
2024	J	`jnl`	Rao-Blackwellising Bayesian Causal Inference. CoRR Christian Toth, Christian Knoll, Franz Pernkopf, Robert Peharz
2024	J	`jnl`	Resource-Efficient Neural Networks for Embedded Systems. J. Mach. Learn. Res. Wolfgang Roth, Günther Schindler, Bernhard Klein, Robert Peharz, Sebastian Tschiatschek, Holger Fröning, Franz Pernkopf, Zoubin Ghahramani
2024	J	`jnl`	What is the Relationship between Tensor Factorizations and Circuits (and How Can We Exploit it)? CoRR Lorenzo Loconte, Antonio Mari, Gennaro Gala, Robert Peharz, Cassio de Campos, Erik Quaeghebeur, Gennaro Vessio, Antonio Vergari
2023	A	`conf`	Bayesian Structure Scores for Probabilistic Circuits. AISTATS Yang Yang, Gennaro Gala, Robert Peharz
2023	J	`jnl`	Bayesian Structure Scores for Probabilistic Circuits. CoRR Yang Yang, Gennaro Gala, Robert Peharz
2023	A*	`conf`	Continuous Mixtures of Tractable Probabilistic Models. AAAI Alvaro H. C. Correia, Gennaro Gala, Erik Quaeghebeur, Cassio P. de Campos, Robert Peharz
2023	J	`jnl`	How to Turn Your Knowledge Graph Embeddings into Generative Models via Probabilistic Circuits. CoRR Lorenzo Loconte, Nicola Di Mauro, Robert Peharz, Antonio Vergari
2023	A*	`conf`	How to Turn Your Knowledge Graph Embeddings into Generative Models. NeurIPS Lorenzo Loconte, Nicola Di Mauro, Robert Peharz, Antonio Vergari
2023	J	`jnl`	Probabilistic Integral Circuits. CoRR Gennaro Gala, Cassio P. de Campos, Robert Peharz, Antonio Vergari, Erik Quaeghebeur
2022	A*	`conf`	Active Bayesian Causal Inference. NeurIPS Christian Toth, Lars Lorch, Christian Knoll, Andreas Krause, Franz Pernkopf, Robert Peharz, Julius von Kügelgen
2022	J	`jnl`	Active Bayesian Causal Inference. CoRR Christian Toth, Lars Lorch, Christian Knoll, Andreas Krause, Franz Pernkopf, Robert Peharz, Julius von Kügelgen
2022	J	`jnl`	Conditional sum-product networks: Modular probabilistic circuits via gate functions. Int. J. Approx. Reason. Xiaoting Shao, Alejandro Molina, Antonio Vergari, Karl Stelzner, Robert Peharz, Thomas Liebig, Kristian Kersting
2022	J	`jnl`	Continuous Mixtures of Tractable Probabilistic Models. CoRR Alvaro H. C. Correia, Gennaro Gala, Erik Quaeghebeur, Cassio P. de Campos, Robert Peharz
2021	—	`conf`	Elevating Perceptual Sample Quality in PCs through Differentiable Sampling. Pre-Registration Workshop @ NeurIPS Steven Lang, Martin Mundt, Fabrizio Ventola, Robert Peharz, Kristian Kersting
2020	—	`conf`	Conditional Sum-Product Networks: Imposing Structure on Deep Probabilistic Architectures. PGM Xiaoting Shao, Alejandro Molina, Antonio Vergari, Karl Stelzner, Robert Peharz, Thomas Liebig, Kristian Kersting
2020	A	`conf`	Deep Structured Mixtures of Gaussian Processes. AISTATS Martin Trapp, Robert Peharz, Franz Pernkopf, Carl Edward Rasmussen
2020	A*	`conf`	Einsum Networks: Fast and Scalable Learning of Tractable Probabilistic Circuits. ICML Robert Peharz, Steven Lang, Antonio Vergari, Karl Stelzner, Alejandro Molina, Martin Trapp, Guy Van den Broeck, Kristian Kersting, Zoubin Ghahramani
2020	J	`jnl`	Einsum Networks: Fast and Scalable Learning of Tractable Probabilistic Circuits. CoRR Robert Peharz, Steven Lang, Antonio Vergari, Karl Stelzner, Alejandro Molina, Martin Trapp, Guy Van den Broeck, Kristian Kersting, Zoubin Ghahramani
2020	A*	`conf`	Joints in Random Forests. NeurIPS Alvaro H. C. Correia, Robert Peharz, Cassio P. de Campos
2020	J	`jnl`	Joints in Random Forests. CoRR Alvaro H. C. Correia, Robert Peharz, Cassio P. de Campos
2020	—	`conf`	PS3: Partition-Based Skew-Specialized Sampling for Batch Mode Active Learning in Imbalanced Text Data. ECML/PKDD (5) Ricky Maulana Fajri, Samaneh Khoshrou, Robert Peharz, Mykola Pechenizkiy
2020	J	`jnl`	Resource-Efficient Neural Networks for Embedded Systems. CoRR Wolfgang Roth, Günther Schindler, Matthias Zöhrer, Lukas Pfeifenberger, Robert Peharz, Sebastian Tschiatschek, Holger Fröning, Franz Pernkopf, Zoubin Ghahramani
2020	—	`conf`	Sum-Product Network Decompilation. PGM Cory J. Butz, Jhonatan de S. Oliveira, Robert Peharz
2020	J	`jnl`	Towards Robust Classification with Deep Generative Forests. CoRR Alvaro H. C. Correia, Robert Peharz, Cassio P. de Campos
2019	A*	`conf`	Automatic Bayesian Density Analysis. AAAI Antonio Vergari, Alejandro Molina, Robert Peharz, Zoubin Ghahramani, Kristian Kersting, Isabel Valera
2019	A*	`conf`	Bayesian Learning of Sum-Product Networks. NeurIPS Martin Trapp, Robert Peharz, Hong Ge, Franz Pernkopf, Zoubin Ghahramani
2019	J	`jnl`	Bayesian Learning of Sum-Product Networks. CoRR Martin Trapp, Robert Peharz, Hong Ge, Franz Pernkopf, Zoubin Ghahramani
2019	J	`jnl`	Conditional Sum-Product Networks: Imposing Structure on Deep Probabilistic Architectures. CoRR Xiaoting Shao, Alejandro Molina, Antonio Vergari, Karl Stelzner, Robert Peharz, Thomas Liebig, Kristian Kersting
2019	J	`jnl`	Deep Structured Mixtures of Gaussian Processes. CoRR Martin Trapp, Robert Peharz, Franz Pernkopf, Carl E. Rasmussen
2019	A*	`conf`	Faster Attend-Infer-Repeat with Tractable Probabilistic Models. ICML Karl Stelzner, Robert Peharz, Kristian Kersting
2019	A*	`conf`	Hierarchical Decompositional Mixtures of Variational Autoencoders. ICML Ping Liang Tan, Robert Peharz
2019	—	`conf`	Minimal Random Code Learning: Getting Bits Back from Compressed Model Parameters. ICLR (Poster) Marton Havasi, Robert Peharz, José Miguel Hernández-Lobato
2019	J	`jnl`	Optimisation of Overparametrized Sum-Product Networks. CoRR Martin Trapp, Robert Peharz, Franz Pernkopf
2019	A	`conf`	Random Sum-Product Networks: A Simple and Effective Approach to Probabilistic Deep Learning. UAI Robert Peharz, Antonio Vergari, Karl Stelzner, Alejandro Molina, Martin Trapp, Xiaoting Shao, Kristian Kersting, Zoubin Ghahramani
2019	J	`jnl`	SPFlow: An Easy and Extensible Library for Deep Probabilistic Learning using Sum-Product Networks. CoRR Alejandro Molina, Antonio Vergari, Karl Stelzner, Robert Peharz, Pranav Subramani, Nicola Di Mauro, Pascal Poupart, Kristian Kersting
2019	J	`jnl`	Sum-Product Network Decompilation. CoRR Cory J. Butz, Jhonatan de S. Oliveira, Robert Peharz
2018	J	`jnl`	Automatic Bayesian Density Analysis. CoRR Antonio Vergari, Alejandro Molina, Robert Peharz, Zoubin Ghahramani, Kristian Kersting, Isabel Valera
2018	J	`jnl`	Efficient and Robust Machine Learning for Real-World Systems. CoRR Franz Pernkopf, Wolfgang Roth, Matthias Zöhrer, Lukas Pfeifenberger, Günther Schindler, Holger Fröning, Sebastian Tschiatschek, Robert Peharz, Matthew Mattina, Zoubin Ghahramani
2018	J	`jnl`	Hybrid generative-discriminative training of Gaussian mixture models. Pattern Recognit. Lett. Wolfgang Roth, Robert Peharz, Sebastian Tschiatschek, Franz Pernkopf
2018	J	`jnl`	Learning Deep Mixtures of Gaussian Process Experts Using Sum-Product Networks. CoRR Martin Trapp, Robert Peharz, Carl E. Rasmussen, Franz Pernkopf
2018	J	`jnl`	Minimal Random Code Learning: Getting Bits Back from Compressed Model Parameters. CoRR Marton Havasi, Robert Peharz, José Miguel Hernández-Lobato
2018	J	`jnl`	Probabilistic Deep Learning using Random Sum-Product Networks. CoRR Robert Peharz, Antonio Vergari, Karl Stelzner, Alejandro Molina, Martin Trapp, Kristian Kersting, Zoubin Ghahramani
2018	A*	`conf`	Sum-Product Autoencoding: Encoding and Decoding Representations Using Sum-Product Networks. AAAI Antonio Vergari, Robert Peharz, Nicola Di Mauro, Alejandro Molina, Kristian Kersting, Floriana Esposito
2017	—	`conf`	Encoding and Decoding Representations with Sum- and Max-Product Networks. ICLR (Workshop) Antonio Vergari, Robert Peharz, Nicola Di Mauro, Floriana Esposito
2017	J	`jnl`	On the Latent Variable Interpretation in Sum-Product Networks. IEEE Trans. Pattern Anal. Mach. Intell. Robert Peharz, Robert Gens, Franz Pernkopf, Pedro M. Domingos
2017	A	`conf`	Safe Semi-Supervised Learning of Sum-Product Networks. UAI Martin Trapp, Tamas Madl, Robert Peharz, Franz Pernkopf, Robert Trappl
2017	J	`jnl`	Safe Semi-Supervised Learning of Sum-Product Networks. CoRR Martin Trapp, Tamas Madl, Robert Peharz, Franz Pernkopf, Robert Trappl
2016	A	`conf`	Manual versus Automated: The Challenging Routine of Infant Vocalisation Segmentation in Home Videos to Study Neuro(mal)development. INTERSPEECH Florian B. Pokorny, Robert Peharz, Wolfgang Roth, Matthias Zöhrer, Franz Pernkopf, Peter B. Marschik, Björn W. Schuller
2016	J	`jnl`	On the Latent Variable Interpretation in Sum-Product Networks. CoRR Robert Peharz, Robert Gens, Franz Pernkopf, Pedro M. Domingos
2015	A	`conf`	On Theoretical Properties of Sum-Product Networks. AISTATS Robert Peharz, Sebastian Tschiatschek, Franz Pernkopf, Pedro M. Domingos
2015	A	`conf`	On representation learning for artificial bandwidth extension. INTERSPEECH Matthias Zöhrer, Robert Peharz, Franz Pernkopf
2015	J	`jnl`	Representation Learning for Single-Channel Source Separation and Bandwidth Extension. IEEE ACM Trans. Audio Speech Lang. Process. Matthias Zöhrer, Robert Peharz, Franz Pernkopf
2014	Misc	`conf`	Modeling speech with sum-product networks: Application to bandwidth extension. ICASSP Robert Peharz, Georg Kapeller, Pejman Mowlaee, Franz Pernkopf
2013	—	`conf`	Greedy Part-Wise Learning of Sum-Product Networks. ECML/PKDD (2) Robert Peharz, Bernhard C. Geiger, Franz Pernkopf
2013	—	`conf`	The Most Generative Maximum Margin Bayesian Networks. ICML (3) Robert Peharz, Sebastian Tschiatschek, Franz Pernkopf
2012	A*	`conf`	Exact Maximum Margin Structure Learning of Bayesian Networks. ICML Robert Peharz, Franz Pernkopf
2012	Misc	`conf`	On linear and mixmax interaction models for single channel source separation. ICASSP Robert Peharz, Franz Pernkopf
2012	J	`jnl`	Sparse nonnegative matrix factorization with ℓ Neurocomputing Robert Peharz, Franz Pernkopf
2011	Misc	`conf`	Efficient implementation of probabilistic multi-pitch tracking. ICASSP Michael Wohlmayr, Robert Peharz, Franz Pernkopf
2011	Misc	`conf`	Gain-robust multi-pitch tracking using sparse nonnegative matrix factorization. ICASSP Robert Peharz, Michael Wohlmayr, Franz Pernkopf
2010	A	`conf`	A factorial sparse coder model for single channel source separation. INTERSPEECH Robert Peharz, Michael Stark, Franz Pernkopf, Yannis Stylianou