Conjugate gradient methods form a class of iterative algorithms that are highly effective for solving large‐scale unconstrained optimisation problems. They achieve efficiency by constructing search ...
A big part of AI and Deep Learning these days is the tuning/optimizing of the algorithms for speed and accuracy. Much of today’s deep learning algorithms involve the use of the gradient descent ...
Existing high-dimensional motion planning algorithms are simultaneously overpowered and underpowered. Indomains sparsely populated by obstacles, the heuristics used by sampling-based planners to ...
A thorough understanding of Linear Algebra and Vector Calculus, and strong familiarity with the Python programming language (e.g., basic data manipulation libraries, how to construct functions and ...
AZoOptics on MSN
End-to-end differentiable design of geometric waveguide displays
A novel differentiable approach optimizes geometric waveguide coatings, achieving substantial gains in light efficiency and uniformity for optical AR displays.
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