東華大學圖書館 |

Language: English

Help

回圖書館首頁

手機版館藏查詢

Back

Switch To: Labeled | MARC Mode | ISBD

Neural-symbolic learning and reasoni...

International Conference on Neural-Symbolic Learning and Reasoning (2024 :)

Linked to FindBook

Google Book

Amazon

博客來

Neural-symbolic learning and reasoning = 18th International Conference, NeSy 2024, Barcelona, Spain, September 9-12, 2024 : proceedings.. Part I /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Neural-symbolic learning and reasoning/ edited by Tarek R. Besold ... [et al.].
Reminder of title:	18th International Conference, NeSy 2024, Barcelona, Spain, September 9-12, 2024 : proceedings.
remainder title:	NeSy 2024
other author:	Besold, Tarek R.
corporate name:	International Conference on Neural-Symbolic Learning and Reasoning
Published:	Cham :Springer Nature Switzerland : : 2024.,
Description:	xxiii, 421 p. :ill. (chiefly color), digital ;24 cm.
[NT 15003449]:	Context Helps: Integrating context information with videos in a graph-based HAR framework. -- Assessing Logical Reasoning Capabilities of Encoder-Only Transformer Models. -- Variable Assignment Invariant Neural Networks for Learning Logic Programs. -- ViPro: Enabling and Controlling Video Prediction for Complex Dynamical Scenarios using Procedural Knowledge. -- The Role of Foundation Models in Neuro-Symbolic Learning and Reasoning. -- A semantic loss for ontology classification. -- On the use of Neurosymbolic AI for Defending against Cyber Attacks. -- Bayesian Inverse Graphics for Few-Shot Concept Learning. -- Simple and Effective Transfer Learning for Neuro-Symbolic Integration. -- Ethical Reward Machines. -- Embed2Rule - Scalable Neuro-Symbolic Learning via Latent Space Weak-Labelling. -- ULLER: A Unified Language for Learning and Reasoning. -- Disentangling Visual Priors: Unsupervised Learning of Scene Interpretations with Compositional Autoencoder. -- Probing LLMs for logical reasoning. -- Enhancing Machine Learning Predictions through Knowledge Graph Embeddings. -- Terminating Differentiable Tree Experts. -- Valid Text-to-SQL Generation with Unification-based DeepStochLog. -- Enhancing Geometric Ontology Embeddings for EL++ with Negative Sampling and Deductive Closure Filtering. -- Lattice-preserving ALC ontology embeddings. -- Towards Learning Abductive Reasoning using VSA Distributed Representations. -- Learning to Solve Abstract Reasoning Problems with Neurosymbolic Program Synthesis and Task Generation. -- Leveraging Neurosymbolic AI for Slice Discovery.
Contained By:	Springer Nature eBook
Subject:	Artificial intelligence - Congresses. -
Online resource:	https://doi.org/10.1007/978-3-031-71167-1
ISBN:	9783031711671

Neural-symbolic learning and reasoning = 18th International Conference, NeSy 2024, Barcelona, Spain, September 9-12, 2024 : proceedings.. Part I /
Neural-symbolic learning and reasoning18th International Conference, NeSy 2024, Barcelona, Spain, September 9-12, 2024 : proceedings.Part I /[electronic resource] :NeSy 2024edited by Tarek R. Besold ... [et al.]. - Cham :Springer Nature Switzerland :2024. - xxiii, 421 p. :ill. (chiefly color), digital ;24 cm. - Lecture notes in computer science,149790302-9743 ;. - Lecture notes in computer science,14979..

Context Helps: Integrating context information with videos in a graph-based HAR framework. -- Assessing Logical Reasoning Capabilities of Encoder-Only Transformer Models. -- Variable Assignment Invariant Neural Networks for Learning Logic Programs. -- ViPro: Enabling and Controlling Video Prediction for Complex Dynamical Scenarios using Procedural Knowledge. -- The Role of Foundation Models in Neuro-Symbolic Learning and Reasoning. -- A semantic loss for ontology classification. -- On the use of Neurosymbolic AI for Defending against Cyber Attacks. -- Bayesian Inverse Graphics for Few-Shot Concept Learning. -- Simple and Effective Transfer Learning for Neuro-Symbolic Integration. -- Ethical Reward Machines. -- Embed2Rule - Scalable Neuro-Symbolic Learning via Latent Space Weak-Labelling. -- ULLER: A Unified Language for Learning and Reasoning. -- Disentangling Visual Priors: Unsupervised Learning of Scene Interpretations with Compositional Autoencoder. -- Probing LLMs for logical reasoning. -- Enhancing Machine Learning Predictions through Knowledge Graph Embeddings. -- Terminating Differentiable Tree Experts. -- Valid Text-to-SQL Generation with Unification-based DeepStochLog. -- Enhancing Geometric Ontology Embeddings for EL++ with Negative Sampling and Deductive Closure Filtering. -- Lattice-preserving ALC ontology embeddings. -- Towards Learning Abductive Reasoning using VSA Distributed Representations. -- Learning to Solve Abstract Reasoning Problems with Neurosymbolic Program Synthesis and Task Generation. -- Leveraging Neurosymbolic AI for Slice Discovery.

This book constitutes the refereed proceedings of the 18th International Conference on Neural-Symbolic Learning and Reasoning, NeSy 2024, held in Barcelona, Spain during September 9-12th, 2024. The 30 full papers and 18 short papers were carefully reviewed and selected from 89 submissions, which presented the latest and ongoing research work on neurosymbolic AI. Neurosymbolic AI aims to build rich computational models and systems by combining neural and symbolic learning and reasoning paradigms. This combination hopes to form synergies among their strengths while overcoming their complementary weaknesses.

ISBN: 9783031711671

Standard No.: 10.1007/978-3-031-71167-1doiSubjects--Topical Terms:

606815
Artificial intelligence
--Congresses.

LC Class. No.: Q334

Dewey Class. No.: 006.3

Neural-symbolic learning and reasoning = 18th International Conference, NeSy 2024, Barcelona, Spain, September 9-12, 2024 : proceedings.. Part I /
LDR:03439nmm a2200361 a 4500 001 2374888
003 DE-He213
005 20240910130221.0
006 m d
007 cr nn 008maaau
008 241231s2024 sz s 0 eng d
020 $a 9783031711671 $q (electronic bk.)
020 $a 9783031711664 $q (paper)
024 7 $a 10.1007/978-3-031-71167-1 $2 doi
035 $a 978-3-031-71167-1
040 $a GP $c GP
041 0 $a eng
050 4 $a Q334
072 7 $a UMZ $2 bicssc
072 7 $a COM051230 $2 bisacsh
072 7 $a UMZ $2 thema
082 0 4 $a 006.3 $2 23
090 $a Q334 $b .I61 2024
111 2 $a International Conference on Neural-Symbolic Learning and Reasoning $n (18th : $d 2024 : $c Barcelona, Spain) $3 3723983
245 1 0 $a Neural-symbolic learning and reasoning $h [electronic resource] : $b 18th International Conference, NeSy 2024, Barcelona, Spain, September 9-12, 2024 : proceedings. $n Part I / $c edited by Tarek R. Besold ... [et al.].
246 3 $a NeSy 2024
260 $a Cham : $b Springer Nature Switzerland : $b Imprint: Springer, $c 2024.
300 $a xxiii, 421 p. : $b ill. (chiefly color), digital ; $c 24 cm.
490 1 $a Lecture notes in computer science, $x 0302-9743 ; $v 14979
490 1 $a Lecture notes in artificial intelligence
505 0 $a Context Helps: Integrating context information with videos in a graph-based HAR framework. -- Assessing Logical Reasoning Capabilities of Encoder-Only Transformer Models. -- Variable Assignment Invariant Neural Networks for Learning Logic Programs. -- ViPro: Enabling and Controlling Video Prediction for Complex Dynamical Scenarios using Procedural Knowledge. -- The Role of Foundation Models in Neuro-Symbolic Learning and Reasoning. -- A semantic loss for ontology classification. -- On the use of Neurosymbolic AI for Defending against Cyber Attacks. -- Bayesian Inverse Graphics for Few-Shot Concept Learning. -- Simple and Effective Transfer Learning for Neuro-Symbolic Integration. -- Ethical Reward Machines. -- Embed2Rule - Scalable Neuro-Symbolic Learning via Latent Space Weak-Labelling. -- ULLER: A Unified Language for Learning and Reasoning. -- Disentangling Visual Priors: Unsupervised Learning of Scene Interpretations with Compositional Autoencoder. -- Probing LLMs for logical reasoning. -- Enhancing Machine Learning Predictions through Knowledge Graph Embeddings. -- Terminating Differentiable Tree Experts. -- Valid Text-to-SQL Generation with Unification-based DeepStochLog. -- Enhancing Geometric Ontology Embeddings for EL++ with Negative Sampling and Deductive Closure Filtering. -- Lattice-preserving ALC ontology embeddings. -- Towards Learning Abductive Reasoning using VSA Distributed Representations. -- Learning to Solve Abstract Reasoning Problems with Neurosymbolic Program Synthesis and Task Generation. -- Leveraging Neurosymbolic AI for Slice Discovery.
520 $a This book constitutes the refereed proceedings of the 18th International Conference on Neural-Symbolic Learning and Reasoning, NeSy 2024, held in Barcelona, Spain during September 9-12th, 2024. The 30 full papers and 18 short papers were carefully reviewed and selected from 89 submissions, which presented the latest and ongoing research work on neurosymbolic AI. Neurosymbolic AI aims to build rich computational models and systems by combining neural and symbolic learning and reasoning paradigms. This combination hopes to form synergies among their strengths while overcoming their complementary weaknesses.
650 0 $a Artificial intelligence $v Congresses. $3 606815
650 1 4 $a Software Engineering. $3 890874
650 2 4 $a Artificial Intelligence. $3 769149
700 1 $a Besold, Tarek R. $3 2133339
710 2 $a SpringerLink (Online service) $3 836513
773 0 $t Springer Nature eBook
830 0 $a Lecture notes in computer science, $x 0302-9743 ; $v 14979. $3 3723984
830 0 $a Lecture notes in artificial intelligence. $3 3382562
856 4 0 $u https://doi.org/10.1007/978-3-031-71167-1
950 $a Computer Science (SpringerNature-11645)