Results 41 to 50 of about 81,262 (253)

Lifted Variable Elimination for Probabilistic Logic Programming

, 2014
Lifted inference has been proposed for various probabilistic logical frameworks in order to compute the probability of queries in a time that depends on the size of the domains of the random variables rather than the number of instances.
Bellodi, Elena, Costa, Vitor Santos, Lamma, Evelina, Riguzzi, Fabrizio, Zese, Riccardo   +4 more
core   +1 more source

CHR(PRISM)-based Probabilistic Logic Learning

, 2010
PRISM is an extension of Prolog with probabilistic predicates and built-in support for expectation-maximization learning. Constraint Handling Rules (CHR) is a high-level programming language based on multi-headed multiset rewrite rules.
Abdennadher, Boenn, Christiansen, Christiansen, De Koninck, Duck, Frühwirth, Getoor, JON SNEYERS, JOOST VENNEKENS, Kameya, Pearl, TAISUKE SATO, Vennekens, WANNES MEERT, YOSHITAKA KAMEYA   +15 more
core   +2 more sources

Improving Candidate Quality of Probabilistic Logic Models [PDF]

, 2018
Many real-world phenomena exhibit both relational structure and uncertainty. Probabilistic Inductive Logic Programming (PILP) uses Inductive Logic Programming (ILP) extended with probabilistic facts to produce meaningful and interpretable models for real-
, , Dries, Anton, Rocha, Ricardo
core   +1 more source

All‐in‐One Analog AI Hardware: On‐Chip Training and Inference with Conductive‐Metal‐Oxide/HfOx ReRAM Devices

Advanced Functional Materials, EarlyView.
An all‐in‐one analog AI accelerator is presented, enabling on‐chip training, weight retention, and long‐term inference acceleration. It leverages a BEOL‐integrated CMO/HfOx ReRAM array with low‐voltage operation (<1.5 V), multi‐bit capability over 32 states, low programming noise (10 nS), and near‐ideal weight transfer.
Donato Francesco Falcone, Victoria Clerico, Wooseok Choi, Tommaso Stecconi, Folkert Horst, Laura Bégon‐Lours, Matteo Galetta, Antonio La Porta, Nikhil Garg, Fabien Alibart, Bert Jan Offrein, Valeria Bragaglia   +11 more
wiley   +1 more source

Autonomous Behavior Selection For Self-driving Cars Using Probabilistic Logic Factored Markov Decision Processes

Applied Artificial Intelligence
We propose probabilistic logic factored Markov decision processes (PL-fMDPs) as a behavior selection scheme for self-driving cars. Probabilistic logic combines logic programming with probability theory to achieve clear, rule-based knowledge descriptions ...
Héctor Avilés, Marco Negrete, Alberto Reyes, Rubén Machucho, Karelly Rivera, Gloria de-la-Garza, Alberto Petrilli   +6 more
doaj   +1 more source

Distributional logic programming for Bayesian knowledge representation [PDF]

, 2016
We present a formalism for combining logic programming and its flavour of nondeterminism with probabilistic reasoning. In particular, we focus on representing prior knowledge for Bayesian inference.
Angelopoulos, Nikolaos, Cussens, James
core   +2 more sources

Photoswitching Conduction in Framework Materials

Advanced Functional Materials, EarlyView.
This mini‐review summarizes recent advances in state‐of‐the‐art proton and electron conduction in framework materials that can be remotely and reversibly switched on and off by light. It discusses the various photoswitching conduction mechanisms and the strategies employed to enhance photoswitched conductivity.
Helmy Pacheco Hernandez, Stefan Hecht, Wolfgang Wenzel, Lars Heinke, Mariana Kozlowska   +4 more
wiley   +1 more source

Probabilistic Programming Concepts [PDF]

, 2013
A multitude of different probabilistic programming languages exists today, all extending a traditional programming language with primitives to support modeling of complex, structured probability distributions.
De Raedt, Luc, Kimmig, Angelika
core  

2D Magnetic and Topological Quantum Materials and Devices for Ultralow Power Spintronics

Advanced Functional Materials, EarlyView.
2D magnets and topological quantum materials enable ultralow‐power spintronics by combining robust magnetic order with symmetry‐protected, Berry‐curvature‐driven transport. Fundamentals of 2D anisotropy and spin‐orbit‐coupling induced band inversion are linked to scalable growth and vdW stacking.
Brahmdutta Dixit, Yifei Yang, Shawn Li, Yu‐Chia Chen, Qi Jia, Jian‐Ping Wang   +5 more
wiley   +1 more source

Stable Model Counting and Its Application in Probabilistic Logic Programming [PDF]

, 2014
Model counting is the problem of computing the number of models that satisfy a given propositional theory. It has recently been applied to solving inference tasks in probabilistic logic programming, where the goal is to compute the probability of given ...
Aziz, Rehan Abdul, Chu, Geoffrey, Muise, Christian, Stuckey, Peter   +3 more
core   +1 more source