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augmentor

Image augmentation library in Python for machine learning.

autolab_core

Core utilities for Berkeley AutoLab.

awesome-deeplearning-resources

Deep Learning and deep reinforcement learning research papers and some codes

baselines

OpenAI Baselines: high-quality implementations of reinforcement learning algorithms

bayesian-modelling-in-python

A python tutorial on bayesian modeling techniques (PyMC3)

bayesopt

BayesOpt: A toolbox for bayesian optimization, experimental design and stochastic bandits.

control

A repository for control benchmarking code

deepbayes-2018

Seminars DeepBayes Summer School 2018

ensembleclassification

This toolbox provides some combination methods to fuse an ensemble of classifiers

featureselection

Feature Selection

gpis

Gaussian Process Implicit Surface and Contact-level Grasp Planning

gpis-1

Work on Gaussian Process Implicit Surfaces

gps

Guided Policy Search

gpucb

Simple implementation of GP-UCB algorithm.

gqcnn

Python modules for GQ-CNN training and deployment, with ROS integration

grasp-rectangle-labelling

A labelling tool for grasp rectangles.

grasp-synergy

Grasp Synergies (aka eigengrasps): compute, store, and command low-dimensional grasp representations.

grasp_execution

grasping

guided-policy-search

Implementation is mostly based on Sergey Levine work (http://www.eecs.berkeley.edu/~svlevine/).

hand_dapg

Repository to accompany arXiv:1709.10087 (RSS 2018 paper)

icra19-lfd-tutorial-exercises

Set of exercises accompanying the ICRA 2019 Tutorial on Dynamical System based Learning from Demonstration: https://epfl-lasa.github.io/TutorialICRA2019.io/

kalman

Some Python Implementations of the Kalman Filter

kuka-lpvds-tasks

This package contains execution code for LPV-DS tasks from Nadia's CoRL (2018) paper using the DS-impedance controller for the KUKA LWR 4+ robot in simulation (gazebo) and real robot.

libfreenect2

Open source drivers for the Kinect for Windows v2 device

lstm-autoencoder

LSTM-Autoencoder and LSTM-Predictor in Tensorflow

machine-learning_tams

models

Models built with TensorFlow

multi-contact-grasping

This project implements a simulated grasp-and-lift process in V-REP using the Barrett Hand, with an interface through a python remote API.

navi_deeprl

Aim to use deep reinforcement learning to realize obstacle avoidance.