research
∙
07/15/2023
Intuitive Access to Smartphone Settings Using Relevance Model Trained by Contrastive Learning
The more new features that are being added to smartphones, the harder it...
share
research
∙
07/15/2023
Safe Formulas in the General Theory of Stable Models
Safe first-order formulas generalize the concept of a safe rule, which p...
research
∙
07/15/2023
Elementary Sets for Logic Programs
By introducing the concepts of a loop and a loop formula, Lin and Zhao s...
research
∙
07/15/2023
First-Order Stable Model Semantics with Intensional Functions
In classical logic, nonBoolean fluents, such as the location of an objec...
research
∙
07/15/2023
NeurASP: Embracing Neural Networks into Answer Set Programming
We present NeurASP, a simple extension of answer set programs by embraci...
research
∙
07/15/2023
Leveraging Large Language Models to Generate Answer Set Programs
Large language models (LLMs), such as GPT-3 and GPT-4, have demonstrated...
research
∙
07/15/2023
Coupling Large Language Models with Logic Programming for Robust and General Reasoning from Text
While large language models (LLMs), such as GPT-3, appear to be robust a...
research
∙
07/10/2023
Learning to Solve Constraint Satisfaction Problems with Recurrent Transformer
Constraint satisfaction problems (CSPs) are about finding values of vari...
research
∙
07/10/2023
Injecting Logical Constraints into Neural Networks via Straight-Through Estimators
Injecting discrete logical constraints into neural network learning is o...
research
∙
05/04/2023
Learning Missing Modal Electronic Health Records with Unified Multi-modal Data Embedding and Modality-Aware Attention
Electronic Health Record (EHR) provides abundant information through var...
research
∙
10/29/2022
Self-supervised predictive coding and multimodal fusion advance patient deterioration prediction in fine-grained time resolution
In the Emergency Department (ED), accurate prediction of critical events...
research
∙
09/13/2022
Moving from 2D to 3D: volumetric medical image classification for rectal cancer staging
Volumetric images from Magnetic Resonance Imaging (MRI) provide invaluab...
research
∙
03/27/2022
Bunched LPCNet2: Efficient Neural Vocoders Covering Devices from Cloud to Edge
Text-to-Speech (TTS) services that run on edge devices have many advanta...
research
∙
09/18/2019
Strong Equivalence for LPMLN Programs
LPMLN is a probabilistic extension of answer set programs with the weigh...
research
∙
07/31/2019
Bridging Commonsense Reasoning and Probabilistic Planning via a Probabilistic Action Language
To be responsive to dynamically changing real-world environments, an int...
research
∙
06/21/2019
Explainable Fact Checking with Probabilistic Answer Set Programming
One challenge in fact checking is the ability to improve the transparenc...
research
∙
04/01/2019
Elaboration Tolerant Representation of Markov Decision Process via Decision-Theoretic Extension of Probabilistic Action Language pBC+
We extend probabilistic action language pBC+ with the notion of utility ...
research
∙
01/22/2019
Fully Convolutional Network-based Multi-Task Learning for Rectum and Rectal Cancer Segmentation
In this study, we present a fully automatic method to segment both rectu...
research
∙
01/22/2019
Multi-Task Learning with a Fully Convolutional Network for Rectum and Rectal Cancer Segmentation
In a rectal cancer treatment planning, the location of rectum and rectal...
research
∙
08/14/2018
Weight Learning in a Probabilistic Extension of Answer Set Programs
LPMLN is a probabilistic extension of answer set programs with the weigh...
research
∙
05/02/2018
Translating LPOD and CR-Prolog2 into Standard Answer Set Programs
Logic Programs with Ordered Disjunction (LPOD) is an extension of standa...
research
∙
05/02/2018
A Probabilistic Extension of Action Language BC+
We present a probabilistic extension of action language BC+. Just like B...
research
∙
07/20/2017
Representing Hybrid Automata by Action Language Modulo Theories
Both hybrid automata and action languages are formalisms for describing ...
research
∙
07/19/2017
Computing LPMLN Using ASP and MLN Solvers
LPMLN is a recent addition to probabilistic logic programming languages....
research
∙
06/28/2016
On the Semantic Relationship between Probabilistic Soft Logic and Markov Logic
Markov Logic Networks (MLN) and Probabilistic Soft Logic (PSL) are widel...
research
∙
01/18/2014
Reformulating the Situation Calculus and the Event Calculus in the General Theory of Stable Models and in Answer Set Programming
Circumscription and logic programs under the stable model semantics are ...
research
∙
01/16/2014
First-Order Stable Model Semantics and First-Order Loop Formulas
Lin and Zhaos theorem on loop formulas states that in the propositional ...
research
∙
12/20/2013
A Functional View of Strong Negation in Answer Set Programming
The distinction between strong negation and default negation has been us...
research
∙
01/08/2013
Two New Definitions of Stable Models of Logic Programs with Generalized Quantifiers
We present alternative definitions of the first-order stable model seman...
research
∙
10/18/2012
Module Theorem for The General Theory of Stable Models
The module theorem by Janhunen et al. demonstrates how to provide a modu...
research
∙
03/23/2011
Representing First-Order Causal Theories by Logic Programs
Nonmonotonic causal logic, introduced by Norman McCain and Hudson Turner...
research
∙
12/28/2010