activity
20172026
most citedSPFlow: An Easy and Extensible Library for Deep Probabilistic Learning using Sum-Product Networks

32 citations · 38 across the 11 of their papers we have counts for

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16 papers · 1 filter

cs.LG2025

Deep Polynomial Chaos Expansion

Johannes Exenberger, Sascha Ranftl, Robert Peharz

Polynomial chaos expansion (PCE) is a classical and widely used surrogate modeling technique in physical simulation and uncertainty quantification. By taking a linear combination o…

cs.LG20251 cited

Exact Soft Analytical Side-Channel Attacks using Tractable Circuits

Thomas Wedenig, Rishub Nagpal, Gaëtan Cassiers +2

Detecting weaknesses in cryptographic algorithms is of utmost importance for designing secure information systems. The state-of-the-art soft analytical side-channel attack (SASCA)…

cs.LG2024

What is the Relationship between Tensor Factorizations and Circuits (and How Can We Exploit it)?

Lorenzo Loconte, Antonio Mari, Gennaro Gala +5

This paper establishes a rigorous connection between circuit representations and tensor factorizations, two seemingly distinct yet fundamentally related areas. By connecting these…

cs.LG2024

One-Shot Federated Learning with Bayesian Pseudocoresets

Tim d'Hondt, Mykola Pechenizkiy, Robert Peharz

Optimization-based techniques for federated learning (FL) often come with prohibitive communication cost, as high dimensional model parameters need to be communicated repeatedly be…

cs.LG2024

Effective Bayesian Causal Inference via Structural Marginalisation and Autoregressive Orders

Christian Toth, Christian Knoll, Franz Pernkopf +1

The traditional two-stage approach to causal inference first identifies a single causal model (or equivalence class of models), which is then used to answer causal queries. However…

cs.LG2023

Probabilistic Integral Circuits

Gennaro Gala, Cassio de Campos, Robert Peharz +2

Continuous latent variables (LVs) are a key ingredient of many generative models, as they allow modelling expressive mixtures with an uncountable number of components. In contrast,…