Spain

ECAI 2020

A Knowledge-driven Approach to Explaining Black-box Models

neural symbolic reasoning

ontologies

explainable ai

ECAI2020 featured a full programme of technical papers, as well as many AI-related events of interest for researchers, students and all attendants who are interested on contemporary AI, including:




**An extensive programme of workshops, tutorials, and invited speakers**

**The Prestigious Applications of Intelligent Systems conference (PAIS)**

**The Frontiers in AI track sessions**

**The Lab To Market event**

**The Women in AI time**

**The EU Challenges forum**

… and many more!

ECAI 2020 featured a full programme of technical papers, as well as many AI-related events of interest for researchers, students and all attendants who are interested on contemporary AI.

technical paper

Accounting for Observer’s Partial Observability in Stochastic Goal Recognition Design: Messing with the Marauder’s Map

Learning Conjunctive Information   of Signals in Multi-sensor Systems

Tree search for the Sequential Ordering Problem

Fully-Convolutional Intensive Feature Flow Neural Network for Text Recognition

Multi-Stage Transfer Learning with an Application to Selection Process

Improving Supervised Superpixel-Based Codebook Representations by Local Convolutional Features

Incorporating Semantic Dependencies Extracted from Knowledge Graphs into Joint Inference template-based Information Extraction

On Measuring Inconsistency in Relational Databases with Denial Constraints

Classifying the classifier: dissecting the weight space of neural networks

Is hardness inherent in computational problems? Performance of human and electronic computers on random instances of the 0-1 knapsack problem.

https://d3smihljt9218e.cloudfront.net/transcript/1183/subtitle/6edda6b5ddb32ff48daa0af7684115e7.vtt

English (automatic)

A Knowledge-driven Approach to Explaining Black-box Models

Downloads

Next from ECAI 2020

Accounting for Observer’s Partial Observability in Stochastic Goal Recognition Design: Messing with the Marauder’s Map

Similar lecture

Ontology Focusing: Knowledge-enriched Databases on Demand

A Knowledge-driven Approach to Explaining Black-box Models

.css-70qvj9{display:-webkit-box;display:-webkit-flex;display:-ms-flexbox;display:flex;-webkit-align-items:center;-webkit-box-align:center;-ms-flex-align:center;align-items:center;}Downloads

Next from ECAI 2020

Accounting for Observer’s Partial Observability in Stochastic Goal Recognition Design: Messing with the Marauder’s Map

Similar lecture

Ontology Focusing: Knowledge-enriched Databases on Demand

Downloads