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glouppe

Add differentiable coverage probability regularizer

11

Resolve https://github.com/probabilists/lampe/issues/14

macio232

Implement differentiable coverage probability regularizer

1

### Description The method described in [Calibrating Neural Simulation-Based Inference with Differentiable Coverage Probability](https://arxiv.org/abs/2310.13402) paper. ### Implementation New loss class in the `inference` module, similar to the [NRELoss](https://lampe.readthedocs.io/en/stable/api/lampe.inference.html#lampe.inference.NRELoss) ->[BNRELoss](https://lampe.readthedocs.io/en/stable/api/lampe.inference.html#lampe.inference.BNRELoss) enhancement....

macio232

Deal with time-dependent or time-series data

12

Hi, Thanks for the wonderful toolkit for simulation-based inference. I am learning it and found it very helpful with my work. I took a look at the examples in tutorial...

Jice-Zeng

Differences in batched vs. non-batched FMPE log_prob

5

### Description When computing the log probability with FMPE's log_prob method, the resulting probability values depend on the other input elements in the batch. The change I saw was in...

LGro