Probabilistic sampling for physics: finding needles in a field of high-dimensional haystacks

Session

Colloquium

Sep 6, 2023, 10:00 AM

Institut Pascal

42. Multiscale Interaction Models of Physical Energies and Deep Networks - Stéphane Mallat (ENS Paris)

9/6/23, 10:00 AM

Building probabilistic models and sampling complex physical fields is an outstanding issue, despite remarkable numerical results of deep networks. Relying on the renormalization group approach, we show that the curse of dimensionality can be avoided by separating variabilites at multiple scales in wavelet bases. The main difficulty is to model interactions across scales. We show that these...

32. Probabilistic forecast of extreme heat waves and climate tipping points using neural networks and rare event simulations

Freddy BOUCHET (ENS, LMD, IPSL)

9/14/23, 3:30 PM

Rare events are of primarily importance for understanding the impact of climate change. The first class are extreme events which have devastating impacts; the second are rare trajectories which lead to bifurcations and drastic changes of the climate system configurations and tipping points. However, because those events are too rare and realistic models are too complex, they cannot be computed...

38. Rare events, large deviation and sampling

Alberto ROSSO (LPTMS-CNRS)

9/20/23, 3:30 PM

In many systems exceptional events can have a crucial impact, while the routine is peaceful and with no consequences. Well known examples are the earthquakes in the Earth's lithosphere or the events of extreme weather. Predicting their magnitude or their occurrence rate is a major challenge for human security and economy. Large deviation theory is the branch of probabilities that adresses...