Denoiser_Encoder-With-DNcnn VS Pytorch-PCGrad

Compare Denoiser_Encoder-With-DNcnn vs Pytorch-PCGrad and see what are their differences.

Denoiser_Encoder-With-DNcnn

this project is created based on state of the art model Dncnn . This is a simple implementation of image denoising (by AmzadHossainrafis)
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Denoiser_Encoder-With-DNcnn Pytorch-PCGrad
1 1
1 265
- -
10.0 1.8
almost 2 years ago almost 3 years ago
Python Python
- BSD 3-clause "New" or "Revised" License
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Denoiser_Encoder-With-DNcnn

Posts with mentions or reviews of Denoiser_Encoder-With-DNcnn. We have used some of these posts to build our list of alternatives and similar projects.

Pytorch-PCGrad

Posts with mentions or reviews of Pytorch-PCGrad. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2022-03-11.

What are some alternatives?

When comparing Denoiser_Encoder-With-DNcnn and Pytorch-PCGrad you can also consider the following projects:

pytorch-grad-norm - Pytorch implementation of the GradNorm. GradNorm addresses the problem of balancing multiple losses for multi-task learning by learning adjustable weight coefficients.

minimalRL - Implementations of basic RL algorithms with minimal lines of codes! (pytorch based)

PPO-PyTorch - Minimal implementation of clipped objective Proximal Policy Optimization (PPO) in PyTorch

cleanrl - High-quality single file implementation of Deep Reinforcement Learning algorithms with research-friendly features (PPO, DQN, C51, DDPG, TD3, SAC, PPG)

muzero-general - MuZero

pytorch-a2c-ppo-acktr-gail - PyTorch implementation of Advantage Actor Critic (A2C), Proximal Policy Optimization (PPO), Scalable trust-region method for deep reinforcement learning using Kronecker-factored approximation (ACKTR) and Generative Adversarial Imitation Learning (GAIL).

pytorch-learn-reinforcement-learning - A collection of various RL algorithms like policy gradients, DQN and PPO. The goal of this repo will be to make it a go-to resource for learning about RL. How to visualize, debug and solve RL problems. I've additionally included playground.py for learning more about OpenAI gym, etc.