Ayush Chopra

same error. Please check.

@natravedrova are you able to obtained similar results (to .mat code) with bin files generated using your implementation?

> > @natravedrova are you able to obtained similar results (to .mat code) with bin files generated using your implementation? > > Yes, I am. > > I tried different...

@ChrisRackauckas this sounds very interesting. Is your paper out yet? keen to see how you work around sampling from discrete distributions w/o reparameterizing. Only other way that comes to mind...

Interesting @ChrisRackauckas. We did similar work with the reparameterization trick to enable differentiable ABMs. Then, we also demonstrate how you can calibrate such large differentiable ABMs with deep neural networks...

this is a good start.. we need to make some changes to runtime. let's discuss on slack

Hi @jzanetti , please use this [yaml file](https://github.com/AgentTorch/AgentTorch/blob/master/agent_torch/models/covid/yamls/config.yaml) file for the runner. That was an older file left behind that we have now removed. Also, I would recommend using the...

Hi @jzanetti Yes, `recovered_and_dead_mask` no gradient because of the logical comparison. To alleviate this, we transform the mask as follows: `new_death_recovered_today = ( current_stages * recovered_and_dead_mask / self.INFECTED_VAR )` Now,...