Artificial Intelligence and the Uncertainty challenge in Fundamental Physics

Session

Benchmark, Datasets and Challenges

29 nov. 2023, 11:30

Présidents de session

Benchmark, Datasets and Challenges

• Jerome Bobin (CEA)

15. Exploring Data Challenges and Leveraging Codabench: A Practical Journey with unsupervised New Physics detection at 40 MHz

Ekaterina Govorkova (MIT)

29/11/2023 11:30

Benchmarks dataset and challenges

This talk delves into our team's experience in orchestrating an unsupervised New Physics detection at 40 MHz, shedding light on the intricacies of design, implementation, and lessons learned.
We challenged the community to develop algorithms for detecting New Physics by reformulating the problem as an out-of-distribution detection task.
We provided datasets with four-vectors of the...

16. Neuroscience ML challenges using CodaBench: Decoding multi-limb trajectories from two-photon calcium imaging

Yuan-Tang Chou (University of Washington, Seattle (US))

29/11/2023 12:00

Data frugal Approaches, Data-centric AI

In this talk, we present the ML challenge using CodaBench for the Neuroscience dataset. The ML challenge is hosted by the Accelerated AI Algorithms for Data-Driven Discovery (A3D3) Institute.

Neural decoding is the process of predicting behavior from brain signals, which is crucial for gaining insights into the functions of various brain regions and for advancing technology, such as the...