The recent progress in Artificial Intelligence and Machine Learning has provided new ways to process large data sets. The new techniques are particularly powerful when dealing with unstructured data or data with complex, non-linear relationships, which are hard to model and analyse with traditional, statistical tools. This has triggered a flurry of activities both in industry and science, developing methods to tackle problems which used to be impossible or extremely hard to deal with.
Due to this situation, we are proposing to organise a meeting where the following key elements would be covered:
The meeting is oriented towards scientists and educators as well as industry and policy makers in R&D.
Editorial Board
Boris Escalante , CViCom-UNAM
Federico Carminati , CERN
Guy Paic , ICN-UNAM
Lukas Nellen , ICN-UNAM
Rafael Mayo , CIEMAT
Steven Schramm , University of Geneva
Zeljko Ivezic , University of Washington
| Sessions |
|---|
| Preface |
| Day 1 |
| Day 2 |
| Day 4 |
| Day 5 |
| Preface |
| Editor’s Note for the Proceedings of the Artificial Intelligence for Science, Industry and Society – AISIS2019 PoS(AISIS2019)048 pdf |
| Day 1 |
| Galaxy Morphology classification using CNN PoS(AISIS2019)006 pdf |
| Generative Model Study for 1+1d-Complex Scalar Field Theory PoS(AISIS2019)007 pdf attachments |
| Studying the parton content of the proton with deep learning models PoS(AISIS2019)008 pdf |
| Online Estimation of Particle Track Parameters based on Neural Networks for the Belle II Trigger System PoS(AISIS2019)010 pdf |
| Generative Adversarial Networks for Fast Simulation: distributed training and generalisation PoS(AISIS2019)012 pdf |
| Portraying Double Higgs at the Large Hadron Collider PoS(AISIS2019)013 pdf |
| Day 2 |
| Trustworthy AI. The AI4EU approach PoS(AISIS2019)014 pdf |
| Regulating Emerging Technologies: Opportunities and Challenges for Latin America PoS(AISIS2019)015 pdf |
| Deep learning for cosmology PoS(AISIS2019)021 pdf |
| A machine learning approach for the feature extraction of pulmonary nodules PoS(AISIS2019)024 pdf attachments |
| Skin Lesion Detection in Dermatological Images using Deep Learning PoS(AISIS2019)025 pdf |
| QUA³CK - A Machine Learning Development Process PoS(AISIS2019)026 pdf |
| Regularization methods vs large training sets PoS(AISIS2019)028 pdf |
| Day 4 |
| Large-Scale Scientific endeavours: the production and dissemination of advance computer sciences knowledge PoS(AISIS2019)040 pdf |
| Machine Learning-Based System for the Availability and Reliability Assessment and Management of Critical Infrastructures (CASO) PoS(AISIS2019)041 pdf |
| Day 5 |
| Robotics, AI and Machine Vision PoS(AISIS2019)043 pdf |
| Machine learning in accelerator physics: applications at the CERN Large Hadron Collider PoS(AISIS2019)044 pdf |
| Policies for Artificial Intelligence in Science and Innovation PoS(AISIS2019)045 pdf |
| Quantum Computing Future-Proofing What Lies Beyond SuperComputing PoS(AISIS2019)047 pdf |