Zackory Erickson's starred repositories
Kalman-and-Bayesian-Filters-in-Python
Kalman Filter book using Jupyter Notebook. Focuses on building intuition and experience, not formal proofs. Includes Kalman filters,extended Kalman filters, unscented Kalman filters, particle filters, and more. All exercises include solutions.
CapsNet-Tensorflow
A Tensorflow implementation of CapsNet(Capsules Net) in paper Dynamic Routing Between Capsules
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).
CapsNet-Keras
A Keras implementation of CapsNet in NIPS2017 paper "Dynamic Routing Between Capsules". Now test error = 0.34%.
awesome-adversarial-machine-learning
A curated list of awesome adversarial machine learning resources
keras-contrib
Keras community contributions
GANotebooks
wgan, wgan2(improved, gp), infogan, and dcgan implementation in lasagne, keras, pytorch
assistive-gym
Assistive Gym, a physics-based simulation framework for physical human-robot interaction and robotic assistance.
GAN-Sandbox
Vanilla GAN implemented on top of keras/tensorflow enabling rapid experimentation & research. Branches correspond to implementations of stable GAN variations (i.e. ACGan, InfoGAN) and other promising variations of GANs like conditional and Wasserstein.
deep-viz-keras
Implementations of some popular Saliency Maps in Keras
bodies-at-rest
Code + Data for CVPR 2020 oral paper "Bodies at Rest: 3D Human Pose and Shape Estimation from a Pressure Image using Synthetic Data."
spectrovision
The SpectroVision dataset and associated code for the paper "Multimodal Material Classification for Robots using Spectroscopy and High Resolution Texture Imaging"
stretch_ros_tutorials
Instructions to run basic functions of a Stretch RE1 robot.
rchi-lab.github.io
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pytorch-a2c-ppo-acktr
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).