Numerical (in)stability of recurrence relations
Explores numerical instability in recurrence relations for special functions like Bessel functions, explaining why forward/reverse computations can be unstable and how to handle it.
Explores numerical instability in recurrence relations for special functions like Bessel functions, explaining why forward/reverse computations can be unstable and how to handle it.
Explains online (one-pass) algorithms using Welford's algorithm for computing mean and variance, plus higher moments and regression.
Explains numerical instability in naive softmax and cross-entropy implementations and provides stable alternatives for deep learning.
A guide to correctly implementing cross-entropy loss in PyTorch for binary and multiclass classification, explaining common pitfalls and best practices.