[null,null,["Last updated 2023-11-21 UTC."],[],[],null,["# tfp.math.log_bessel_kve\n\n\u003cbr /\u003e\n\n|------------------------------------------------------------------------------------------------------------------------------------------|\n| [View source on GitHub](https://github.com/tensorflow/probability/blob/v0.23.0/tensorflow_probability/python/math/bessel.py#L1295-L1320) |\n\nComputes `log(tfp.math.bessel_kve(v, z))`. \n\n tfp.math.log_bessel_kve(\n v, z, name=None\n )\n\n### Used in the notebooks\n\n| Used in the tutorials |\n|----------------------------------------------------------------------------------------------------------------------|\n| - [TFP Release Notes notebook (0.13.0)](https://www.tensorflow.org/probability/examples/TFP_Release_Notebook_0_13_0) |\n\nThis function is a more numerically stable version of\n`log(tfp.math.bessel_kve(v, z))`.\n| **Warning:** Gradients with respect to the first parameter `v` are currently not defined.\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Args ---- ||\n|--------|-----------------------------------------------------------------------------------------------------------------------------------------------------|\n| `v` | Floating-point `Tensor` broadcastable with `z` for which `log(Kve(v, z))` should be computed. `v` is expected to be non-negative. |\n| `z` | Floating-point `Tensor` broadcastable with `v` for which `log(Kve(v, z))` should be computed. If `z` is negative, `v` is expected to be an integer. |\n| `name` | A name for the operation (optional). Default value: `None` (i.e., 'log_bessel_kve'). |\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Returns ------- ||\n|------------------|-------------------------------------------------------------------|\n| `log_bessel_kve` | Log of Exponentially modified Bessel Function of the second kind. |\n\n\u003cbr /\u003e"]]