Spain

ECAI 2020

DRNet: Dissect and Reconstruct the Convolutional Neural Network via Interpretable Manners

sub-net

reconstruct

dissect

convolutional networks

### Artificial Intelligence in Metabolism (AIM)

AIM is a seminar series that will explore the potential of data science in metabolic research. It is hosted by the Novo Nordisk Foundation Center for Basic Metabolic Research (CBMR) at the University of Copenhagen.
The seminar series takes place over three days in June and July, 2021 from 4pm to 5:30 pm CEST.

![](https://assets.underline.io/uploads/markdown_image/1/image/bc89e60b0a0f2d7550c75517a10f2843.png)
**About AIM**

Artificial Intelligence in Metabolism brings together renowned investigators to discuss how cutting edge data science can be best utilized to challenge current dogmas and catalyse better translation in metabolic and biomedical research.

Significant new discoveries in metabolic research increasingly rely on large-scale profiling, data integration and machine learning-based techniques. Not only can these techniques be leveraged to distil novel actionable biological hypotheses to be tested in relevant physiological contexts/clinical settings, they for example enable us to develop predictive tools to more effectively and timely identify at-risk individuals or personalized drugs/interventions. 

At the Novo Nordisk Foundation Center for Basic Metabolic Research (CBMR) we have set up enabling biology platforms that utilize sophisticated metabolomics, single-cell and data integration techniques to enrich our deeply phenotyped and genotyped patient cohorts. These data, along with the associated Danish longitudinal health register information, constitute a unique base to empower current and next generations of scientists to tackle the major questions in metabolic research.

We envision that data and machine learning models will be at the heart of future teams driving novel discoveries in metabolic research, through interdisciplinary approaches involving traditional biomedical scientists alongside data scientists, mathematicians and bioinformaticians.
Please join us in our effort to discuss and incubate new ideas to better explore and model metabolic disease.

![](https://assets.underline.io/uploads/markdown_image/1/image/bc89e60b0a0f2d7550c75517a10f2843.png)



AIM Seminar Series 2021

AIM is a seminar series that will explore the potential of data science in metabolic research. It is hosted by the Novo Nordisk Foundation Center for Basic Metabolic Research (CBMR) at the University of Copenhagen. The seminar series takes place over three days in June and July, 2021 from 4pm to 5:30 pm CEST.

technical paper

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.

Learning Deterministic Automata on Infinite Words

Polynomial Neural Networks and Taylor maps for Dynamical Systems Simulation and Learning

Learning classifier chains using matrix regularization: application to multimorbidity prediction

Abstract Argumentation with Markov Networks

IAD: A Benchmark Dataset and a New Method for Illegal Advertising Classification

Preferences over rankings and how to control them using rewards

Monte Carlo Information-Oriented Planning

Enhanced foraging in robot swarms using collective Lévy walks

General Supervision via Probabilistic Transformations

Generating Ensembles of Multi-Label Classifiers Using Cooperative Coevolutionary Algorithms

https://d3smihljt9218e.cloudfront.net/transcript/992/subtitle/bd5f77d9b72c8e7b6a6749dbd94ec199.vtt

English (automatic)

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Learning Deterministic Automata on Infinite Words

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Learning Deterministic Automata on Infinite Words

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