City, University of London

research

∙ 02/29/2020

Graph Neural Networks Meet Neural-Symbolic Computing: A Survey and Perspective

Neural-symbolic computing has now become the subject of interest of both...

Luis Lamb, et al. ∙

research

∙ 12/10/2021

Logical Boltzmann Machines

The idea of representing symbolic knowledge in connectionist systems has...

Son N. Tran, et al. ∙

research

∙ 11/11/2019

Making Good on LSTMs Unfulfilled Promise

LSTMs promise much to financial time-series analysis, temporal and cross...

Daniel Philps, et al. ∙

research

∙ 12/06/2018

Continuous Learning Augmented Investment Decisions

Investment decisions can benefit from incorporating an accumulated knowl...

Daniel Philps, et al. ∙

research

∙ 12/22/2021

Neural-Symbolic Integration for Interactive Learning and Conceptual Grounding

We propose neural-symbolic integration for abstract concept explanation ...

Benedikt Wagner, et al. ∙

research

∙ 06/30/2022

Implicit U-Net for volumetric medical image segmentation

U-Net has been the go-to architecture for medical image segmentation tas...

Sergio Naval Marimont, et al. ∙

research

∙ 01/10/2020

Network of Steel: Neural Font Style Transfer from Heavy Metal to Corporate Logos

We introduce a method for transferring style from the logos of heavy met...

Aram Ter-Sarkisov, et al. ∙

research

∙ 09/26/2021

Synthetic Data Generation for Fraud Detection using GANs

Detecting money laundering in gambling is becoming increasingly challeng...

Charitos Charitou, et al. ∙

research

∙ 03/19/2020

Layerwise Knowledge Extraction from Deep Convolutional Networks

Knowledge extraction is used to convert neural networks into symbolic de...

Simon Odense, et al. ∙

research

∙ 12/08/2021

Prediction of Adverse Biological Effects of Chemicals Using Knowledge Graph Embeddings

We have created a knowledge graph based on major data sources used in ec...

Erik B. Myklebust, et al. ∙

research

∙ 08/19/2021

Deep Learning-based Spacecraft Relative Navigation Methods: A Survey

Autonomous spacecraft relative navigation technology has been planned fo...

Jianing Song, et al. ∙

research

∙ 09/20/2021

Counterfactual Instances Explain Little

In many applications, it is important to be able to explain the decision...

Adam White, et al. ∙

research

∙ 05/15/2019

Neural-Symbolic Computing: An Effective Methodology for Principled Integration of Machine Learning and Reasoning

Current advances in Artificial Intelligence and machine learning in gene...

Artur d'Avila Garcez, et al. ∙

research

∙ 01/19/2020

Correcting Knowledge Base Assertions

The usefulness and usability of knowledge bases (KBs) is often limited b...

Jiaoyan Chen, et al. ∙

research

∙ 08/08/2019

Measurable Counterfactual Local Explanations for Any Classifier

We propose a novel method for explaining the predictions of any classifi...

Adam White, et al. ∙

research

∙ 10/06/2017

The Recurrent Temporal Discriminative Restricted Boltzmann Machines

The recurrent temporal restricted Boltzmann machine (RTRBM) has been suc...

Son N. Tran, et al. ∙

research

∙ 06/14/2016

Logic Tensor Networks: Deep Learning and Logical Reasoning from Data and Knowledge

We propose Logic Tensor Networks: a uniform framework for integrating au...

Luciano Serafini, et al. ∙

research

∙ 05/24/2017

Logic Tensor Networks for Semantic Image Interpretation

Semantic Image Interpretation (SII) is the task of extracting structured...

Ivan Donadello, et al. ∙

research

∙ 01/18/2017

Reasoning in Non-Probabilistic Uncertainty: Logic Programming and Neural-Symbolic Computing as Examples

This article aims to achieve two goals: to show that probability is not ...

Tarek R. Besold, et al. ∙

research

∙ 05/19/2017

Deep De-Aliasing for Fast Compressive Sensing MRI

Fast Magnetic Resonance Imaging (MRI) is highly in demand for many clini...

Simiao Yu, et al. ∙

research

∙ 07/10/2002

Well-Founded Argumentation Semantics for Extended Logic Programming

This paper defines an argumentation semantics for extended logic program...

Ralf Schweimeier, et al. ∙

research

∙ 08/31/2017

Revisited Experimental Comparison of Node-Link and Matrix Representations

Visualizing network data is applicable in domains such as biology, engin...

Mershack Okoe, et al. ∙

research

∙ 04/25/2017

The Emergence of Consensus: A Primer

The origin of population-scale coordination has puzzled philosophers and...

Andrea Baronchelli, et al. ∙

research

∙ 01/24/2018

Mitigating CSRF attacks on OAuth 2.0 and OpenID Connect

Many millions of users routinely use their Google, Facebook and Microsof...

Wanpeng Li, et al. ∙

research

∙ 04/23/2018

Towards Symbolic Reinforcement Learning with Common Sense

Deep Reinforcement Learning (deep RL) has made several breakthroughs in ...

Artur d'Avila Garcez, et al. ∙

research

∙ 07/23/2018

Undecidability of MSO+"ultimately periodic"

We prove that MSO on ω-words becomes undecidable if allowing to quantify...

Mikołaj Bojańczyk, et al. ∙

research

∙ 11/19/2018

M2U-Net: Effective and Efficient Retinal Vessel Segmentation for Resource-Constrained Environments

In this paper, we present a novel neural network architecture for retina...

Tim Laibacher, et al. ∙

research

∙ 11/27/2018

Improved Speech Enhancement with the Wave-U-Net

We study the use of the Wave-U-Net architecture for speech enhancement, ...

Craig Macartney, et al. ∙

research

∙ 12/04/2018

Feed-Forward Neural Networks Need Inductive Bias to Learn Equality Relations

Basic binary relations such as equality and inequality are fundamental t...

Tillman Weyde, et al. ∙

research

∙ 12/06/2018

Modelling Identity Rules with Neural Networks

In this paper, we show that standard feed-forward and recurrent neural n...

Tillman Weyde, et al. ∙

research

∙ 12/06/2018

Continual Learning Augmented Investment Decisions

Investment decisions can benefit from incorporating an accumulated knowl...

Daniel Philps, et al. ∙

research

∙ 12/19/2018

Progressive Data Science: Potential and Challenges

Data science requires time-consuming iterative manual activities. In par...

Cagatay Turkay, et al. ∙

research

∙ 01/24/2019

OAuthGuard: Protecting User Security and Privacy with OAuth 2.0 and OpenID Connect

Millions of users routinely use Google to log in to websites supporting ...

Wanpeng Li, et al. ∙

research

∙ 02/11/2019

Geometric Multicut

We study the following separation problem: Given a collection of colored...

Mikkel Abrahamsen, et al. ∙

research

∙ 03/14/2019

Constrained Mutual Convex Cone Method for Image Set Based Recognition

In this paper, we propose a method for image-set classification based on...

Naoya Sogi, et al. ∙

research

∙ 04/02/2019

Continuous chain-ladder with paid data

We introduce a model where iid payments generate the traditional paid ru...

Stephan M. Bischofberger, et al. ∙

research

∙ 04/02/2019

Non-Smooth Backfitting for Excess Risk Additive Regression Model with Two Survival Time-Scales

We present a new backfitting algorithm estimating the complex structured...

Munir Hiabu, et al. ∙

research

∙ 05/20/2019

Non-Parametric Estimation of Spot Covariance Matrix with High-Frequency Data

Estimating spot covariance is an important issue to study, especially wi...

Konul Mustafayeva, et al. ∙

research

∙ 06/13/2019

Factors for the Generalisation of Identity Relations by Neural Networks

Many researchers implicitly assume that neural networks learn relations ...

Radha Kopparti, et al. ∙

research

∙ 06/15/2019

Efficient predicate invention using shared "NeMuS"

Amao is a cognitive agent framework that tackles the invention of predic...

Edjard Mota, et al. ∙

research

∙ 06/19/2019

An Ontology-based Approach to Explaining Artificial Neural Networks

Explainability in Artificial Intelligence has been revived as a topic of...

Roberto Confalonieri, et al. ∙

research

∙ 07/10/2019

A Framework for Multiaccess Support for Unreliable Internet Traffic using Multipath DCCP

Mobile nodes are typically equipped with multiple radios and can connect...

Markus Amend, et al. ∙

research

∙ 07/19/2019

Criteria for Rigor in Visualization Design Study

We develop a new perspective on research conducted through visualization...

Miriah Meyer, et al. ∙

research

∙ 08/01/2019

Design by Immersion: A Transdisciplinary Approach to Problem-Driven Visualizations

While previous work exists on how to conduct and disseminate insights fr...

Kyle Wm. Hall, et al. ∙

research

∙ 08/19/2019

Assessing the Safety and Reliability of Autonomous Vehicles from Road Testing

There is an urgent societal need to assess whether autonomous vehicles (...

Xingyu Zhao, et al. ∙

research

∙ 11/28/2019

Words of Estimative Correlation: Studying Verbalizations of Scatterplots

Multimodal approaches where interactive visualization and natural langua...

Rafael Henkin, et al. ∙

research

∙ 03/06/2020

Weight Priors for Learning Identity Relations

Learning abstract and systematic relations has been an open issue in neu...

Kopparti Radha, et al. ∙

research

∙ 03/06/2020

Multi-Time-Scale Convolution for Emotion Recognition from Speech Audio Signals

Robustness against temporal variations is important for emotion recognit...

Eric Guizzo, et al. ∙

research

∙ 02/25/2020

Dividing the Ontology Alignment Task with Semantic Embeddings and Logic-based Modules

Large ontologies still pose serious challenges to state-of-the-art ontol...

Ernesto Jiménez-Ruiz, et al. ∙

research

∙ 03/18/2020

Detection of Pitt-Hopkins Syndrome based on morphological facial features

This work describes an automatic methodology to discriminate between ind...

Elena D'Amato, et al. ∙

City, University of London

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