Foundation Tomislav Lipić
Machine Learning and Applications Workshop
Time: Friday, May 31st 2024
Co-organizer: Rudjer Boskovic Institute (RBI)
Workshop location (next to RBI)
Lecture Hall @ Institute of Physics,
Bijenička Cesta 46, 10000, Zagreb, Croatia
Invited speakers:
Goran Glavaš, University of Würzburg, Germany
Davor Horvatić, Department of Physics, University of Zagreb, Croatia
Jan Nagler, Centre for Human and Machine Intelligence, Frankfurt, Germany
Ivan Vulić, University of Cambridge & PolyAI, UK
Amir Zamir, EPFL, Switzerland
Nino Antulov-Fantulin, Aisot Technologies AG & ETH Zürich, Switzerland
Maria Brbić, EPFL, Switzerland
Tomislav Šmuc, Rudjer Boskovic Institute, Zagreb, Croatia
Nima Dehmamy, IBM Research, USA
Schedule:
09:00 - 09:30
Registration
09:30 - 09:40
Welcome note / About Tomislav Lipić Foundation
Tamara Lipić / Marko Poljak
09:40 - 09:50
Workshop outline
Maria Brbić, Nino Antulov-Fantulin
09:50 - 10:00
About Rudjer Boskovic Institute (RBI)
David Matthew Smith / Ivančica Bogdanović Radović
10:00 - 10:20
Machine Learning at RBI
Tomislav Šmuc
Coffee break & networking
10:40 - 11:10
Deep Convolutional Interpreter for time series
Davor Horvatić
11:10 - 11:40
Towards AI-driven biomedical discoveries
Maria Brbić
11:40 - 12:10
Yet Another Neural Network for Dynamics
Nino Antulov-Fantulin
Lunch break & networking
14:00 - 14:30
AI for science and science of AI
Nima Dehmamy
14:30 - 15:00
Is Scale the (Only) Answer? On Competitive NLP under Resource
Constraints
Goran Glavaš
15:00 - 15:30
An Incredibly Short Introduction to Modular Deep Learning
Ivan Vulić
Coffee break
15:50 - 16:20
Impact of Ergodicity Breaking on Objectives in ML
Jan Nagler
16:20 - 16:50
Multimodal Foundation Models
Amir Zamir
Closing note
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Admission to the workshop is complimentary, but we have a limited number of spots available. To ensure your spot, please register here. We kindly ask that you register only if you are committed to attending (in physical presence, online participation is not possible). We will close registration, after filling a limited number of spots.