Comments (2)
Hi, yes we used phi_grad initially as were worried about the numerical stability of the gradients in our experiments for different f-divergences, but agreeing with your point, you can use phi and torch autograd
can handle it well
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Got it! Thanks for the explanation.
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Related Issues (19)
- expert datasets HOT 4
- Getting missing args error running train_iq.py examples from run_offline.sh HOT 2
- Critic function is diverging while using SAC HOT 17
- Divergence Issue
- Poor performance on robosuite tasks
- Issue on robosuite tasks
- Offline Learning without access to environment.
- Issues on reproducing MuJoCo results
- Can you provide the expert demo of Carracing-v1 environment?
- Atari results are not reproducible
- Issue on reproduce MuJoCo results HOT 5
- How to judge the convergence HOT 10
- Issue on reproducing pointmaze experiments HOT 1
- Issue on reproduce MuJoCo results-HalfCheetah-v2 HOT 14
- Code for gridworld experiments HOT 3
- Issue on Ant-v2 expertd data and Humanoid-v2 random seed Experiments HOT 1
- Config for expert generation
- Pseudocode and questions
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