Rhys Goodall

Results 41 issues of Rhys Goodall

Having trained a re-calibration model using this library it is not obvious how to actually extract the calibrated uncertainties for the data points. As well as being generally useful it...

enhancement

Sometimes I want to plot a phase diagram and highlight points that are not on the convex hull. It would be nice to be able to give a list of...

If I query a structure with magnetic moments defined i.e. `mp-1228485` and run it through `SpacegroupAnalyzer` then call `get_symmetrized_structure()` it returns ``` SymmetrizedStructure Full Formula (Al12 Cr4 O24) Reduced Formula:...

**Is your feature request related to a problem? Please describe.** It would be nice to be able to pass `matplotlib` axes objects to `PDPlotter` when using the `matplotlib` backend such...

How hard would it be to change the construction of the local environment graph to be end-to-end differentiable? This would involve the neighbour list function inside pymatgen being refactored to...

The pre-trained MEGNet cannot handle materials with atoms that are isolated with 5\AA, when using BOSWR the GP can select such structures as candidates what happens? I cannot find any...

Many ML models perform better when trying to fit approximately Gaussian distributions of values - as such using a power-transform as part of the AMM workflow might lead to a...

### Describe the workflow you want to enable For single output RFR trained with the squared error criterion the impurity of the leaves can be used as a crude but...

New Feature
Needs Decision
RFC

```python ________________________________________________________________________________________________ test_mamba_inner_fn[False-True-128-itype0-wtype0] ________________________________________________________________________________________________ is_variable_B = False, is_variable_C = True, seqlen = 128, itype = torch.float32, wtype = torch.float32 @pytest.mark.parametrize('wtype', [torch.float32, torch.complex64]) # @pytest.mark.parametrize('wtype', [torch.complex64]) # @pytest.mark.parametrize('itype', [torch.float32, torch.float16, torch.bfloat16])...

Several issues have requested the ability to input initial state but several of these have often been closed by those posting without the issue being resolved. This issue simply collates...