AI4Physics event: Differential Programming at the Frontiers of Computation

Differentiable programming revolutionizes computational modeling by enabling the seamless integration of gradient-based optimization into complex systems, fostering advancements across scientific and engineering disciplines. The workshop will mix theoretical lectures and practical exercises, with a focus on the latter. I will illustrate how automatic differentiation provides exact derivatives calculated numerically with almost no computational overhead, powering all modern machine learning. Once models are fully differentiable, the conceptual leap to differentiable programming will be done, to "make the world differentiable". Finally, I will illustrate how the computational and environmental challenges of large-scale computing models require shifting to new information encoding paradigmas, delving into introductory notions and exercises on spiking networks powered by neuromorphic computing platforms and on quantum machine learning.

See also Differentiable Programming for the Frontiers of Computation: Methods and New Perspectives and Differential Programming at the Frontiers of Computation.