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09/20/2023
Colour Passing Revisited: Lifted Model Construction with Commutative Factors
Lifted probabilistic inference exploits symmetries in a probabilistic mo...
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04/28/2022
Derivation of Learning Rules for Coupled Principal Component Analysis in a Lagrange-Newton Framework
We describe a Lagrange-Newton framework for the derivation of learning r...
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10/18/2021
Lifting DecPOMDPs for Nanoscale Systems – A Work in Progress
DNA-based nanonetworks have a wide range of promising use cases, especia...
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07/18/2020
Improved Convergence Speed of Fully Symmetric Learning Rules for Principal Component Analysis
Fully symmetric learning rules for principal component analysis can be d...
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05/24/2020
Derivation of Symmetric PCA Learning Rules from a Novel Objective Function
Neural learning rules for principal component / subspace analysis (PCA /...
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03/25/2020
Derivation of Coupled PCA and SVD Learning Rules from a Newton Zero-Finding Framework
In coupled learning rules for PCA (principal component analysis) and SVD...
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01/07/2020
Exploring Unknown Universes in Probabilistic Relational Models
Large probabilistic models are often shaped by a pool of known individua...
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11/16/2019
Taming Reasoning in Temporal Probabilistic Relational Models
Evidence often grounds temporal probabilistic relational models over tim...
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07/02/2018
Answering Hindsight Queries with Lifted Dynamic Junction Trees
The lifted dynamic junction tree algorithm (LDJT) efficiently answers fi...
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07/02/2018
Preventing Unnecessary Groundings in the Lifted Dynamic Junction Tree Algorithm
The lifted dynamic junction tree algorithm (LDJT) efficiently answers fi...
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07/02/2018
Fusing First-order Knowledge Compilation and the Lifted Junction Tree Algorithm
Standard approaches for inference in probabilistic formalisms with first...
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11/01/2016
Detecting Affordances by Visuomotor Simulation
The term "affordance" denotes the behavioral meaning of objects. We prop...
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07/18/2016
