32 citations · 172 across the 28 of their papers we have counts for
31 papers
Acquisition Function-Guided Generation for Bayesian Optimization over Discrete Spaces
Tommaso Ancilli, Thomas Wedenig, Henry Moss +1
Bayesian optimization (BO) over discrete spaces is challenging due to missing gradients and the sparsity of valid solutions. Latent-space BO sidesteps both issues by fitting a surr…
Probabilistic Circuits as Reasoning Machines in Artificial Intelligence (Part I)
Robert Peharz
This cumulative habilitation thesis studies probabilistic circuits (PCs) as a powerful and tractable framework for reasoning and learning under uncertainty in artificial intelligen…
The RAIL Principles for Neurosymbolic AI: Reasoning, Assurances, Interfacing and Learning
Agnese Chiatti, Michael Cochez, Cristina Cornelio +14
Neurosymbolic AI systems that integrate machine learning and symbolic reasoning are rapidly gaining attention. They complement the data-intensive statistical approaches of neural n…
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…
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)…
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…