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pro vyhledávání: '"Wang, BenJie"'
Circuits based on sum-product structure have become a ubiquitous representation to compactly encode knowledge, from Boolean functions to probability distributions. By imposing constraints on the structure of such circuits, certain inference queries b
Externí odkaz:
http://arxiv.org/abs/2412.05481
Probabilistic circuits (PCs) is a unifying representation for probabilistic models that support tractable inference. Numerous applications of PCs like controllable text generation depend on the ability to efficiently multiply two circuits. Existing m
Externí odkaz:
http://arxiv.org/abs/2411.12256
Most methods for neural network verification focus on bounding the image, i.e., set of outputs for a given input set. This can be used to, for example, check the robustness of neural network predictions to bounded perturbations of an input. However,
Externí odkaz:
http://arxiv.org/abs/2408.09262
Large Language Models (LLMs) are typically shipped with tokenizers that deterministically encode text into so-called canonical token sequences, to which the LLMs assign probability values. One common assumption is that the probability of a piece of t
Externí odkaz:
http://arxiv.org/abs/2408.08541
Publikováno v:
In Proceedings of the UAI Workshop on Tractable Probabilistic Modeling (TPM), 2024
A probabilistic circuit (PC) succinctly expresses a function that represents a multivariate probability distribution and, given sufficient structural properties of the circuit, supports efficient probabilistic inference. Typically a PC computes the p
Externí odkaz:
http://arxiv.org/abs/2408.04229
Autor:
Wang, Benjie, Broeck, Guy Van den
Probabilistic circuits are a unifying representation of functions as computation graphs of weighted sums and products. Their primary application is in probabilistic modeling, where circuits with non-negative weights (monotone circuits) can be used to
Externí odkaz:
http://arxiv.org/abs/2408.00876
Autor:
Amarilli, Antoine, Arenas, Marcelo, Choi, YooJung, Monet, Mikaël, Broeck, Guy Van den, Wang, Benjie
This document is an introduction to two related formalisms to define Boolean functions: binary decision diagrams, and Boolean circuits. It presents these formalisms and several of their variants studied in the setting of knowledge compilation. Last,
Externí odkaz:
http://arxiv.org/abs/2404.09674
Discovering the underlying relationships among variables from temporal observations has been a longstanding challenge in numerous scientific disciplines, including biology, finance, and climate science. The dynamics of such systems are often best des
Externí odkaz:
http://arxiv.org/abs/2311.03309
Neural network verification mainly focuses on local robustness properties, which can be checked by bounding the image (set of outputs) of a given input set. However, often it is important to know whether a given property holds globally for the input
Externí odkaz:
http://arxiv.org/abs/2305.03686
Autor:
Wang, Benjie, Kwiatkowska, Marta
Probabilistic circuits (PCs) are a class of tractable probabilistic models, which admit efficient inference routines depending on their structural properties. In this paper, we introduce md-vtrees, a novel structural formulation of (marginal) determi
Externí odkaz:
http://arxiv.org/abs/2304.08278