Conveners
Machine Learning, Data Science & Interdisciplinary applications
- Samir Suweiss (University of Padova)
Machine Learning, Data Science & Interdisciplinary applications
- Samir Suweiss (University of Padova)
Timescales characterize how fast the observables change in time. In neuro science, they can be estimated from the measured activity and can be used, for example, as a signature of the memory trace in the activations. Inferring the
timescales seems to be an easy task; however, I will show you how the timescales are subject to a statistical bias that is impossible to remove by a simple...
In a rapidly changing world, facing an increasing number of socioeconomic, health and environmental crises, physics of data and complex systems can help us to assess and quantify
vulnerabilities, and to monitor and achieve the UN Sustainable Development Goals. In this talk, I will provide an overview of the main areas of applications where physics of data and
complex systems has shown its...
In physics the data that is acquired in experiments are highly-controlled and often taken with specific goals in mind. However, the notion of a “Physics of Data” is about using mathematical tools developed in physics to understand data acquired in more open-ended and uncontrolled environments. As the data acquisition process becomes more opaque and distant from any particular purpose, we have...
