• Outreach event “Machine Learning, Spesa & ChatGPT, cosa hanno in comune”
  by Valerio Pagliarino
  9 February 2023
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  New Machine Learning courses from the MLJC in A.Y. 2022-23
  by Letizia Pizzini
  20 January 2023
  An outstanding opportunity to learn Machine Learning with an “hands-on” approach and get in touch with the Machine Learning Journal Club association. Introduction to Machine Learning Language: Italian Corso articolato in 10 lezioni di circa 2h tenuto presso il Dipartimento di Fisica in orario 16-18.Dopo una prima introduzione al Machine Learning, il corso si focalizzerà sulla comprensione e l’implementazione di algoritmi in linguaggio Python, dai più semplici quali Linear e Logistic Regression […]
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  MLJC mentioned in TG Regione Piemonte
  by Letizia Pizzini
  9 January 2023
  On 7th January 2023, RAI TG Regione Piemonte mentioned the Machine Learning Journal Club, its activities and the future Centre for Artificial Intelligence that is expected to be hosted in Turin. https://www.rainews.it/tgr/piemonte/video/2023/01/fermo-al-palo-il-centro-per-lintelligenza-artificiale-f0c4f3cf-320c-462e-a5d5-2d0663710e49.html https://www.rainews.it/tgr/piemonte/notiziari/video/2023/01/TGR-Piemonte-del-07012023-ore-1930-165576ba-cdc6-4766-b5c0-27a1d9267e11.html
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  Report from NeurIPS 2022, New Orleans, LA (USA)
  by Valerio Pagliarino
  10 December 2022
  Presentation at NeurIPS 2022, “Symmetries and Geometry in Neural Representations” Workshop (NeurReps) Workshop website | NeurIPS website Last week, some of our members went to New Orleans for the thirty-sixth Conference on Neural Information Processing Systems, one of the biggest gatherings of machine learning researchers from all over the world. Having the chance to bring part of our association to NeurIPS 2022 was a great honour for us. We took part in […]
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  MLJC project in Geometric DL accepted at NeurIPS 2022, New Orleans (USA)
  by Valerio Pagliarino
  30 October 2022
  We are delighted to announce that a group from MLJC including Luca Bottero, Francesco Calisto and Valerio Pagliarino will present their work at the world-leading conference NeurIPS 2022 (Neural Information Processing Systems) in the Neur-Reps (https://www.neurreps.org/) (Symmetries and Geometry in Neural Representations) workshop. The conference will take place in New Orleans, Louisiana (USA) from November, 27th to December 3rd. The project is inserted in the landscape of Geometric Deep Learning (GDL), a […]
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  Presentation of MLJC Projects for A.Y. 2022/23 10th November, Physics Dept. of the University of Turin
  by Simone Azeglio
  29 October 2022
  The Machine Learning Journal Club is happy to invite you to the event “MLJC – Presentation of projects and activities for the Academic Year 2022-23“. MLJC members will present the key projects and activites currently under development and they will interact with students, researchers and AI enthusiasts for extending our network and opportunities to everyone that is interested in collaborating with us. A large number of highly interactive short talks will allow […]
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  Activity Report 2021 published
  by Valerio Pagliarino
  11 May 2022
  The Machine Learning Journal Club is pleased to publish the Annual Activity Report 2021 where the most relevant scientific and outreach activity of the past year is presented. This report is a great occasion to thank the several people and institutions that contributed to our activities with their expertise, resources and support.

The Machine Learning Journal Club participated in the SHARPER – European Researchers’ Night in Turin on September 24th 2021, organized by the University of Turin and Politecnico of Turin, in the beautiful frame of the Castello del Valentino. The title of the stand was “MACHINE LEARNING E L’INTELLIGENZA ARTIFICIALE DEL FUTURO”. At our stand we presented projects spacing from Brain Computer Interfaces to Scientific Machine Learning.

Brain computer Interfaces

The MedicAI team showcased the new BCI hardware from OpenBCI that will allow the team to run custom experiments in order to acquire data for training, validation and testing of new advanced algorithms for EEG signal classification. These last are fundamental for critical applications, for example in allowing communication or the use of computers for people that cannot use their hands because of diseases. [Open the page]

Scientific Machine Learning

We presented an overview on our past Scientific Machine Learning projects that have the goal to create accurate and efficient models of natural phenomena by merging the knowledge coming from the physics-based approaches using differential equations and the data-driven approaches. In particular we showcased the work “Physics-Informed Machine Learning Simulator for Wildfire Propagation” and our contribution to “NeuralPDE: Automating Physics-Informed Neural Networks (PINNs) with Error Approximations” [Open the page]

Real Time Scientific Machine Learning

We presented an electronics based on a SoC with GPU acceleration , an FPGA and a large amount of inputs and outputs that allows to run machine learning algorithsm not only “offline” on dataset already saved on the hard drive, but also in real time on data coming from sensors. In this way it is possible to deploy machine learning applications where it is required by the model to trigger decisions with a very low latency (thanks to the FPGA-based neural network inference). In this project the final goal is the realization of adaptive control for dynamical systems that can merge knowledge coming from physics priors and sensor fusion. This project is still “work in progress”! [Open the page]

Videos

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