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Probabilistic reasoning and statistical analysis in TensorFlow
Hi, Bayesian Vector Autoregression is quite popular in macroeconomics, if your team could set up an example for this, that would be good for economic researchers from MATLAB to Python....
when will the inverse cdf of these kinda distribution quantile be implemented? I have nightly version installed but found quantile not implemented.
I am using the **DenseFlipOut** layer, I see that it has a mean_normal distribution over the weights and the biases by default, but I was wondering how these distributions are...
Hi, I have been tinkering with the `SoftmaxCentered` bijector but I would like help understanding how the determinant of the Jacobian is calculated. I've already found the function [SoftmaxCentered._inverse_log_det_jacobian](https://github.com/tensorflow/probability/blob/v0.23.0/tensorflow_probability/python/bijectors/softmax_centered.py#L122), which...
While the [documentation states](https://www.tensorflow.org/probability/api_docs/python/tfp/distributions/Empirical#args) that > The first k dimensions index into a batch of independent distributions this is not the case for the implementation. As can be seen from...
I am trying to learn the parameters of a Weibull distribution, but after the first iteration the gradients turn None: ```python import tensorflow as tf from tensorflow_probability import distributions as...
**Feature** Add the ability to create "always-on" dropout layers as proposed [here](https://arxiv.org/abs/1703.04977). **Current behavior/state.** `tf.keras.layers.Dropout` operates differently at train and test time. It randomly drops node during training while simply...
Hi, I noticed the `quantile()` function of `tfd.Empirical` raises the following error: `AttributeError: 'function' object has no attribute 'percentile'`. ```python import tensorflow_probability as tfp tfd = tfp.distributions tfd.Empirical(samples=[1,2,3]).quantile(value=[0.1, 0.5]) >>>......
Hi, I'm facing a memory leak issue with TFP distributions. Specifically, I have a custom function that samples from a Categorical distribution and returns the output: ``` def compute_categorical_distribution(classes_pred,dtype=np.int8,validate_args=True): #...
Hi all, I have a batch of data and want to conduct the Kalman filter for each observation set. My data is `observations =(batch, num_time_lens, feature_dim)` so I use `tf.vectorized_map`...