Robert Peharz
22 papers · 2013–2025 · 9 venues · across top CS/AI venues
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Achievements
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πΊοΈ Taxonomy Completionist (34) π Conference Polyglot Β· Silver π Academic Marathon Β· Half π Interdisciplinary Bridge Β· Bronze π£ Hot Topic Early Bird
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Grand Slam
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Triple Crown
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Prolific Year Β· Productive
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Century Club Β· Bronze
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Conference Pioneer
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Keyword Collector
(94)
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Research topics
Machine Learning
(19)
Artificial Intelligence
(15)
Bayesian & Probabilistic Β· Artificial Intelligence
(11)
Optimization & Theory
(10)
Core Methods
(9)
Deep Learning
(8)
Models
(8)
Bayesian & Probabilistic Β· Machine Learning
(7)
Core AI
(5)
Learning Types
(3)
Computer Vision
(2)
Analysis
(2)
Application Areas
(2)
Architectures
(2)
Mathematics & Optimization
(1)
Keywords
sum-product network
(7)
bayesian inference
(5)
probabilistic circuit
(5)
generative model
(5)
graphical model
(4)
variational inference
(3)
density estimation
(3)
probabilistic modeling
(3)
variational autoencoder
(3)
gaussian process
(3)
tractable inference
(3)
neural network
(2)
structure learning
(2)
bayesian causal inference
(2)
probabilistic graphical model
(2)
support vector machine
(2)
bayesian network
(2)
anomaly detection
(2)
random forest
(2)
uncertainty quantification
(1)
Papers
Effective Bayesian Causal Inference via Structural Marginalisation and Autoregressive Orders
AISTATS 2025
Exact Soft Analytical Side-Channel Attacks using Tractable Circuits
ICML 2024
Probabilistic Integral Circuits
AISTATS 2024
Resource-Efficient Neural Networks for Embedded Systems
JMLR 2024
Bayesian Structure Scores for Probabilistic Circuits
AISTATS 2023
Continuous Mixtures of Tractable Probabilistic Models
AAAI 2023
How to Turn Your Knowledge Graph Embeddings into Generative Models
NeurIPS 2023
Active Bayesian Causal Inference
NeurIPS 2022
Conditional Sum-Product Networks: Imposing Structure on Deep Probabilistic Architectures
PGM 2020
Deep Structured Mixtures of Gaussian Processes
AISTATS 2020
Einsum Networks: Fast and Scalable Learning of Tractable Probabilistic Circuits
ICML 2020
Joints in Random Forests
NeurIPS 2020
Sum-Product Network Decompilation
PGM 2020
Automatic Bayesian Density Analysis
AAAI 2019
Bayesian Learning of Sum-Product Networks
NeurIPS 2019
Faster Attend-Infer-Repeat with Tractable Probabilistic Models
ICML 2019
Hierarchical Decompositional Mixtures of Variational Autoencoders
ICML 2019
Minimal Random Code Learning: Getting Bits Back from Compressed Model Parameters
ICLR 2019
Random Sum-Product Networks: A Simple and Effective Approach to Probabilistic Deep Learning
UAI 2019
Manual versus Automated: The Challenging Routine of Infant Vocalisation Segmentation in Home Videos to Study Neuro(mal)development
Interspeech 2016
On Theoretical Properties of Sum-Product Networks
AISTATS 2015
The Most Generative Maximum Margin Bayesian Networks
ICML 2013