Code for ICLR 2022 Paper (HyperDQN: A Randomized Exploration Method for Deep Reinforcement Learning)
-
Updated
Nov 28, 2023 - Python
#
iclr-2022
Here are 2 public repositories matching this topic...
Updated fork of Natural Posterior Network with support for PyTorch 2.x. Removed the LightKit dependency and integrated essential components locally to ensure full compatibility and standalone operation.
bayesian uncertainty-estimation bayesian-neural-networks pytorch-implementation pytorch-2 predictive-uncertainty torch-2 iclr-2022 natpn natural-posterior-network
-
Updated
Nov 19, 2025 - Python
Improve this page
Add a description, image, and links to the iclr-2022 topic page so that developers can more easily learn about it.
Add this topic to your repo
To associate your repository with the iclr-2022 topic, visit your repo's landing page and select "manage topics."