Topic: "denoising-autoencoder"
rhythmcao/unsup-two-stage-semantic-parsing
Source code and data for paper ``Unsupervised Dual Paraphrasing for Two-stage Semantic Parsing" in ACL 2020.
Language: Python - Size: 1.03 MB - Last synced at: over 2 years ago - Pushed at: almost 3 years ago - Stars: 5 - Forks: 0
ian0/donkeycar-rl
Teaching the Donkey car to drive a track in the simulator using State Representation Learning and different Reinforcement Learning Algorithms including Deep Q-Network, Soft Actor-Critic and Proximal Policy Optimization Algorithms.
Language: Jupyter Notebook - Size: 117 MB - Last synced at: over 2 years ago - Pushed at: over 3 years ago - Stars: 2 - Forks: 0
SURESHBEEKHANI/Autoencoders
This project is a practice implementation of an autoencoder, The primary use case for this autoencoder is for anomaly detection in sales data, but it can be adapted for other purposes. The autoencoder compresses the input data into a lower-dimensional representation and then reconstructs the original input from this representation.
Language: Jupyter Notebook - Size: 477 KB - Last synced at: about 2 months ago - Pushed at: about 2 months ago - Stars: 1 - Forks: 0
antonio-f/Autoencoders_TF2
Autoencoders with TensorFlow 2
Language: Jupyter Notebook - Size: 1.99 MB - Last synced at: 3 months ago - Pushed at: over 4 years ago - Stars: 1 - Forks: 1
antonio-f/Autoencoders
Autoencoders test from Coursera's Advanced Machine Learning - Intro to Deep Learning course.
Language: Jupyter Notebook - Size: 1.19 MB - Last synced at: 3 months ago - Pushed at: over 5 years ago - Stars: 1 - Forks: 0