https://pypi.org/project/omnibias-jax/ Recent updates to the Python Package Index for omnibias-jax en https://pypi.org/project/omnibias-jax/0.4.0/ JAX backend for omnibias: closed-form n-th derivative activation kernels (sigmoid via Eulerian polynomials, tanh via Legendre, Gaussian via Hermite), neural-field Laplacian / Hessian primitives, and Born-Oppenheimer derivative tools for variational quantum Monte Carlo. vardan@derivon.ai Sun, 13 Sep 2026 17:24:57 GMT