UZH ML Workshop

Session

Presentations

16 Nov 2020, 13:10

online (UZH, Zurich)

17. Learning Vision-based Agile Flight

Antonio Loquercio (Robotics group UZH)

16/11/2020, 13:10

Autonomous quadrotors will soon play a major role in search-and-rescue and remote-inspection missions, where a fast response is crucial. Quadrotors have the potential to navigate quickly through unstructured environments, enter and exit buildings through narrow gaps, and fly through collapsed buildings. However, their speed and maneuverability are still far from those of birds and human...

18. Application of machine learning methods in gravitational wave astrophysics

Dixeena Lopez (UZH)

16/11/2020, 13:40

Identifying the presence of a gravitational wave transient buried in non-stationary, non-Gaussian noise which can often contain spurious noise transients (glitches) is a very challenging task. For a given data set, transient gravitational wave searches produce a corresponding list of triggers that indicate the possible presence of a gravitational wave signal. These triggers are often the...

19. Identifying Anomalous Shared E-Scooter Patterns Using Unsupervised Deep Learning

Prof. Alan MacEachren (The Pennsylvania State University), Yanan Xin (ETH)

16/11/2020, 14:30

Dockless e-scooters have flooded into many cities as a new type of shared vehicle, giving transportation planners great challenges in providing timely support towards setting up necessary infrastructure and regulations. Despite the need, there have been relatively few studies on shared dockless e-scooters and even less attention to identifying anomalous usage patterns. These studies are an...

30. Machine Learning techniques in gamma-ray astrophysics

Dr Alison Mitchell (University of Zurich)

16/11/2020, 15:00

Gamma-ray Astrophysics concerns the most powerful particle accelerators in the universe and the origins of cosmic rays. In recent years, the field has continuously progressed from studies of individual sources to large-scale surveys. Due to the detection technique used by ground-based gamma-ray telescopes, machine learning has enabled considerable progress in recent years.
The data volumes...

16. Which shoes fit this dress? Using product images to infer “perfect pairings” without supervision

Mr Luca Gaegauf (University of Zurich), Markus Meierer (UZH)

16/11/2020, 15:30

Product recommendations are omnipresent and contribute significantly to the revenue of online retail businesses. Nevertheless, customers often complain about the quality of recommendations. A possible explanation is that the requirements of existing approaches are not always met. The increasing speed of product assortment changes challenges collaborative filter techniques, which are subject to...

20. Machine learning in quantum chemistry

Michela Pauletti (UZH)

16/11/2020, 16:20

In the past, potential energy functions for atomistic simulations have been derived using physical approximations whenever the direct application of electronic structure methods has been too demanding. For years people kept fitting potentials to develop new force field, cheap and reasonably accurate methods to carry out computer simulations.
Recent advances in machine learning offer new...

21. Searching for new physics with Variational Autoencoders

Barry Dillon (Heidelberg U.)

16/11/2020, 16:50

In this talk I will discuss my research into the use of variaitonal
autoencoders to search for new physics anomalies in di-jet events at the Large Hadron Collider. Given the nature of the workshop I will also give a broader overview of the challenge this work addresses, and discuss prospects for the use of such methods in the future.

22. Financial documents processing with NLP

Markus Leippold (UZH), Qian Wang (UZH)

16/11/2020, 17:20

Processing financial documents quickly and incorporating updated information (e.g. earning calls, news and financial filings) are the keys to successful investment decision. However, as the volume of financial documents explodes, the number of financial analysts is far from enough compared with the demand for efficiency and coverage, especially during peak seasons. With the progress of Natural...