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jsspencer avatar jsspencer commented on July 19, 2024

You need to use the same settings in networks.fermi_net as you used in training. In particular, the envelope_type and full_det arguments should match cfg.network.envelope_type and cfg.network.full_det.

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 avatar commented on July 19, 2024

is envelope_type and full_det in networks.fermi_net for the current Neon result the same as the current settings in cfg.network.envelope_type and cfg.network.full_det? If not, what should these values be?

Also, what are the param settings to reproduce the other elements? A list of params to reproduce the results would be helpful :)

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jsspencer avatar jsspencer commented on July 19, 2024

By "current Neon result" do you mean from the Phys Rev Research paper? That was produced with the TF version (which is essentially deprecated). The isotropic envelope setting was introduced in the NeurIPS workshop paper, which gives motivation for this and comparison to the full envelope. All results published before then used the full envelope setting.

The full_det setting is experimental. Set it to False to match the published results.

For neon, neither of these settings will make a substantial difference to the final energy within statistical errors. Note your batch size is very small and might limit the accuracy you achieve.

Please refer to our papers for the settings used in the models. The PRR paper used the same set of configuration options for all experiments, except where noted, and this broadly matches the current defaults (except for full_det and envelope_type).

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