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Hinge-Loss Markov Random Fields and Probabilistic Soft Logic

Hinge-Loss Markov Random Fields and Probabilistic Soft Logic

17 May 2015
Stephen H. Bach
Matthias Broecheler
Bert Huang
Lise Getoor
    TPM
    AI4CE
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Papers citing "Hinge-Loss Markov Random Fields and Probabilistic Soft Logic"

50 / 118 papers shown
Title
Relational Reasoning Networks
Relational Reasoning Networks
G. Marra
Michelangelo Diligenti
Francesco Giannini
NAI
29
4
0
01 Jun 2021
Classifying Argumentative Relations Using Logical Mechanisms and
  Argumentation Schemes
Classifying Argumentative Relations Using Logical Mechanisms and Argumentation Schemes
Yohan Jo
Seo-Jin Bang
Chris Reed
Eduard H. Hovy
21
36
0
17 May 2021
Human Schema Curation via Causal Association Rule Mining
Human Schema Curation via Causal Association Rule Mining
Noah Weber
Anton Belyy
Nils Holzenberger
Rachel Rudinger
Benjamin Van Durme
19
0
0
18 Apr 2021
Probabilistic Box Embeddings for Uncertain Knowledge Graph Reasoning
Probabilistic Box Embeddings for Uncertain Knowledge Graph Reasoning
Xuelu Chen
Michael Boratko
Muhao Chen
S. Dasgupta
Xiang Lorraine Li
Andrew McCallum
34
45
0
09 Apr 2021
Modular Design Patterns for Hybrid Learning and Reasoning Systems: a
  taxonomy, patterns and use cases
Modular Design Patterns for Hybrid Learning and Reasoning Systems: a taxonomy, patterns and use cases
M. V. Bekkum
M. D. Boer
F. V. Harmelen
André Meyer-Vitali
A. T. Teije
28
68
0
23 Feb 2021
Randomized Deep Structured Prediction for Discourse-Level Processing
Randomized Deep Structured Prediction for Discourse-Level Processing
Manuel Widmoser
Maria Leonor Pacheco
Jean Honorio
Dan Goldwasser
BDL
35
7
0
25 Jan 2021
Clinical Temporal Relation Extraction with Probabilistic Soft Logic
  Regularization and Global Inference
Clinical Temporal Relation Extraction with Probabilistic Soft Logic Regularization and Global Inference
Yichao Zhou
Yu Yan
Rujun Han
J. H. Caufield
Kai-Wei Chang
Yizhou Sun
Peipei Ping
Wei Wang
NAI
13
42
0
16 Dec 2020
Neurosymbolic AI: The 3rd Wave
Neurosymbolic AI: The 3rd Wave
Artur Garcez
Luís C. Lamb
NAI
65
292
0
10 Dec 2020
Contrastive Losses and Solution Caching for Predict-and-Optimize
Contrastive Losses and Solution Caching for Predict-and-Optimize
Maxime Mulamba
Jayanta Mandi
Michelangelo Diligenti
M. Lombardi
Víctor Bucarey
Tias Guns
23
48
0
10 Nov 2020
Modeling Content and Context with Deep Relational Learning
Modeling Content and Context with Deep Relational Learning
Maria Leonor Pacheco
Dan Goldwasser
NAI
41
34
0
20 Oct 2020
Machine Knowledge: Creation and Curation of Comprehensive Knowledge
  Bases
Machine Knowledge: Creation and Curation of Comprehensive Knowledge Bases
Gerhard Weikum
Luna Dong
Simon Razniewski
Fabian M. Suchanek
25
125
0
24 Sep 2020
Neural Networks Enhancement with Logical Knowledge
Neural Networks Enhancement with Logical Knowledge
Alessandro Daniele
Luciano Serafini
NAI
24
3
0
13 Sep 2020
HyperFair: A Soft Approach to Integrating Fairness Criteria
HyperFair: A Soft Approach to Integrating Fairness Criteria
Charles Dickens
Rishika Singh
Lise Getoor
33
4
0
05 Sep 2020
Foundations of Reasoning with Uncertainty via Real-valued Logics
Foundations of Reasoning with Uncertainty via Real-valued Logics
Ronald Fagin
Ryan Riegel
Alexander G. Gray
NAI
LRM
AI4CE
19
9
0
06 Aug 2020
Logical Neural Networks
Logical Neural Networks
Ryan Riegel
Alexander G. Gray
F. Luus
Naweed Khan
Ndivhuwo Makondo
...
S. Ikbal
Hima P. Karanam
S. Neelam
Ankita Likhyani
S. Srivastava
NAI
11
148
0
23 Jun 2020
An Integer Linear Programming Framework for Mining Constraints from Data
An Integer Linear Programming Framework for Mining Constraints from Data
Tao Meng
Kai-Wei Chang
27
6
0
18 Jun 2020
RelEx: A Model-Agnostic Relational Model Explainer
RelEx: A Model-Agnostic Relational Model Explainer
Yue Zhang
David DeFazio
Arti Ramesh
16
104
0
30 May 2020
Learning and Reasoning for Robot Dialog and Navigation Tasks
Learning and Reasoning for Robot Dialog and Navigation Tasks
Keting Lu
Shiqi Zhang
Peter Stone
Xiaoping Chen
14
5
0
20 May 2020
Exploring Probabilistic Soft Logic as a framework for integrating
  top-down and bottom-up processing of language in a task context
Exploring Probabilistic Soft Logic as a framework for integrating top-down and bottom-up processing of language in a task context
Johannes Dellert
14
3
0
15 Apr 2020
OptTyper: Probabilistic Type Inference by Optimising Logical and Natural
  Constraints
OptTyper: Probabilistic Type Inference by Optimising Logical and Natural Constraints
Irene Vlassi Pandi
Earl T. Barr
Andrew D. Gordon
Charles Sutton
22
29
0
01 Apr 2020
Struct-MMSB: Mixed Membership Stochastic Blockmodels with Interpretable
  Structured Priors
Struct-MMSB: Mixed Membership Stochastic Blockmodels with Interpretable Structured Priors
Yue Zhang
Arti Ramesh
16
2
0
21 Feb 2020
Learning Fairness-aware Relational Structures
Learning Fairness-aware Relational Structures
Yue Zhang
Arti Ramesh
FaML
18
7
0
21 Feb 2020
Relational Neural Machines
Relational Neural Machines
G. Marra
Michelangelo Diligenti
Francesco Giannini
Marco Gori
Marco Maggini
NAI
BDL
25
38
0
06 Feb 2020
Efficient Probabilistic Logic Reasoning with Graph Neural Networks
Efficient Probabilistic Logic Reasoning with Graph Neural Networks
Yuyu Zhang
Xinshi Chen
Yu’an Yang
Arun Ramamurthy
Bo-wen Li
Yuan Qi
Le Song
AI4CE
17
111
0
29 Jan 2020
Estimating Aggregate Properties In Relational Networks With Unobserved
  Data
Estimating Aggregate Properties In Relational Networks With Unobserved Data
Varun R. Embar
S. Srinivasan
Lise Getoor
17
0
0
16 Jan 2020
EGGS: A Flexible Approach to Relational Modeling of Social Network Spam
EGGS: A Flexible Approach to Relational Modeling of Social Network Spam
Jonathan Brophy
Daniel Lowd
17
3
0
14 Jan 2020
Joint Reasoning for Multi-Faceted Commonsense Knowledge
Joint Reasoning for Multi-Faceted Commonsense Knowledge
Yohan Chalier
Simon Razniewski
Gerhard Weikum
LRM
19
25
0
13 Jan 2020
User Profiling Using Hinge-loss Markov Random Fields
User Profiling Using Hinge-loss Markov Random Fields
G. Farnadi
Lise Getoor
Marie-Francine Moens
Martine De Cock
17
2
0
05 Jan 2020
srlearn: A Python Library for Gradient-Boosted Statistical Relational
  Models
srlearn: A Python Library for Gradient-Boosted Statistical Relational Models
Alexander L. Hayes
GP
11
1
0
17 Dec 2019
Deep Learning for Predicting Dynamic Uncertain Opinions in Network Data
Deep Learning for Predicting Dynamic Uncertain Opinions in Network Data
Xujiang Zhao
F. Chen
Jin-Hee Cho
15
14
0
12 Oct 2019
Deep Ordinal Regression for Pledge Specificity Prediction
Deep Ordinal Regression for Pledge Specificity Prediction
Shivashankar Subramanian
Trevor Cohn
Timothy Baldwin
11
7
0
31 Aug 2019
Neural Networks for Relational Data
Neural Networks for Relational Data
Navdeep Kaur
Gautam Kunapuli
Saket Joshi
Kristian Kersting
Sriraam Natarajan
GNN
NAI
11
7
0
28 Aug 2019
T-Norms Driven Loss Functions for Machine Learning
T-Norms Driven Loss Functions for Machine Learning
G. Marra
Francesco Giannini
Michelangelo Diligenti
Marco Maggini
Marco Gori
21
13
0
26 Jul 2019
Probabilistic Approximate Logic and its Implementation in the Logical
  Imagination Engine
Probabilistic Approximate Logic and its Implementation in the Logical Imagination Engine
Mark-Oliver Stehr
Minyoung Kim
C. Talcott
M. Knapp
A. Vertes
21
2
0
25 Jul 2019
Neural Probabilistic Logic Programming in DeepProbLog
Neural Probabilistic Logic Programming in DeepProbLog
Robin Manhaeve
Sebastijan Dumancic
Angelika Kimmig
T. Demeester
Luc de Raedt
NAI
30
542
0
18 Jul 2019
On the relation between Loss Functions and T-Norms
On the relation between Loss Functions and T-Norms
Francesco Giannini
G. Marra
Michelangelo Diligenti
Marco Maggini
Marco Gori
26
7
0
18 Jul 2019
Integrating Knowledge and Reasoning in Image Understanding
Integrating Knowledge and Reasoning in Image Understanding
Somak Aditya
Yezhou Yang
Chitta Baral
OCL
27
40
0
24 Jun 2019
NLProlog: Reasoning with Weak Unification for Question Answering in
  Natural Language
NLProlog: Reasoning with Weak Unification for Question Answering in Natural Language
Leon Weber
Pasquale Minervini
Jannes Munchmeyer
Ulf Leser
Tim Rocktaschel
NAI
LRM
13
94
0
14 Jun 2019
Can Graph Neural Networks Help Logic Reasoning?
Can Graph Neural Networks Help Logic Reasoning?
Yuyu Zhang
Xinshi Chen
Yu’an Yang
Arun Ramamurthy
Bo Li
Yuan Qi
Le Song
NAI
AI4CE
18
13
0
05 Jun 2019
A Boxology of Design Patterns for Hybrid Learning and Reasoning Systems
A Boxology of Design Patterns for Hybrid Learning and Reasoning Systems
F. V. Harmelen
A. T. Teije
6
67
0
29 May 2019
Informed Machine Learning -- A Taxonomy and Survey of Integrating
  Knowledge into Learning Systems
Informed Machine Learning -- A Taxonomy and Survey of Integrating Knowledge into Learning Systems
Laura von Rueden
S. Mayer
Katharina Beckh
B. Georgiev
Sven Giesselbach
...
Rajkumar Ramamurthy
Michal Walczak
Jochen Garcke
Christian Bauckhage
Jannis Schuecker
34
626
0
29 Mar 2019
LYRICS: a General Interface Layer to Integrate Logic Inference and Deep
  Learning
LYRICS: a General Interface Layer to Integrate Logic Inference and Deep Learning
G. Marra
Francesco Giannini
Michelangelo Diligenti
Marco Gori
AI4CE
24
11
0
18 Mar 2019
Knowledge Refinement via Rule Selection
Knowledge Refinement via Rule Selection
Phokion G. Kolaitis
Lucian Popa
Kun Qian
21
1
0
29 Jan 2019
Learning and Reasoning for Robot Sequential Decision Making under
  Uncertainty
Learning and Reasoning for Robot Sequential Decision Making under Uncertainty
S. Amiri
Mohammad Shokrolah Shirazi
Shiqi Zhang
LRM
27
23
0
16 Jan 2019
Integrating Learning and Reasoning with Deep Logic Models
Integrating Learning and Reasoning with Deep Logic Models
G. Marra
Francesco Giannini
Michelangelo Diligenti
Marco Gori
NAI
29
56
0
14 Jan 2019
Spatial Knowledge Distillation to aid Visual Reasoning
Spatial Knowledge Distillation to aid Visual Reasoning
Somak Aditya
Rudra Saha
Yezhou Yang
Chitta Baral
26
14
0
10 Dec 2018
Embedding Uncertain Knowledge Graphs
Embedding Uncertain Knowledge Graphs
X. Chen
Muhao Chen
Weijia Shi
Yizhou Sun
C. Zaniolo
23
116
0
26 Nov 2018
Training Machine Learning Models by Regularizing their Explanations
Training Machine Learning Models by Regularizing their Explanations
A. Ross
FaML
18
0
0
29 Sep 2018
Robot Representation and Reasoning with Knowledge from Reinforcement
  Learning
Robot Representation and Reasoning with Knowledge from Reinforcement Learning
Keting Lu
Shiqi Zhang
Peter Stone
Xiaoping Chen
OffRL
22
18
0
28 Sep 2018
Uncertainty Aware AI ML: Why and How
Uncertainty Aware AI ML: Why and How
Lance M. Kaplan
Federico Cerutti
Murat Sensoy
Alun D. Preece
Paul Sullivan
13
20
0
20 Sep 2018
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