397462521's Stars
dougsm/ggcnn
Generative Grasping CNN from "Closing the Loop for Robotic Grasping: A Real-time, Generative Grasp Synthesis Approach" (RSS 2018)
TianheWu/LGPNet
LGPNet: Alleviating A Few Labeled Data and Large-Scale Network Dilemmas in Grasping Detection
stefan-ainetter/grasp_det_seg_cnn
Code for ICRA21 paper "End-to-end Trainable Deep Neural Network for Robotic Grasp Detection and Semantic Segmentation from RGB".
qgallouedec/panda-gym
Set of robotic environments based on PyBullet physics engine and gymnasium.
Rxzh/DRL_MINES
Files and setup for the training of the robot arm UR3 using DRL algorithms with Tensorflow (CV) and PyTorch (RL).
zhongjieGDUT/DRL_robot
Deep Reiforcemrnt Learning for robotics
kaymen99/Robot-arm-control-with-RL
Robot arm control using reinforcement learning algorithms : DDPG and TD3 with hindsight experience replay (HER)
vaishnavmohit/MAREO
uoe-agents/epymarl
An extension of the PyMARL codebase that includes additional algorithms and environment support
facebookresearch/pyrobot
PyRobot: An Open Source Robotics Research Platform
samasadii/pacman-berkeley
The Pac-Man projects were developed for UC Berkeley's introductory artificial intelligence course, CS 188. They apply an array of AI techniques to playing Pac-Man. However, these projects don't focus on building AI for video games. Instead, they teach foundational AI concepts, such as informed state-space search, probabilistic inference, and reinforcement learning. These concepts underly real-world application areas such as natural language processing, computer vision, and robotics. We designed these projects with three goals in mind. The projects allow students to visualize the results of the techniques they implement. They also contain code examples and clear directions, but do not force students to wade through undue amounts of scaffolding. Finally, Pac-Man provides a challenging problem environment that demands creative solutions; real-world AI problems are challenging, and Pac-Man is too. In our course, these projects have boosted enrollment, teaching reviews, and student engagement. The projects have been field-tested, refined, and debugged over multiple semesters at Berkeley. We are now happy to release them to other universities for educational use.
jonathanleemn/Artifical_Intelligence
CSCI 4511W - Problem solving, search, inference techniques. Knowledge representation. Planning. Machine learning. Robotics. Lisp programming language.
aseem02/Bayesian-Inference
This code base is my introduction and development of implementing bayes theorem for machine learning/Autonomous Vehicle/robotics applications.
mnbf9rca/robond_term2_p1_robotic_inference
project 1 (robotic inference) for term2 of udacity robotics nanodegree nd209
stereoboy/RoboND-Robotic-Inference
shwetaruparel/RoboticInference
RoboticInference
sanjass/RobotLocationInference
ga74kud/causal_inference
Causal Inference
magnusgp/CausalInference
Project in Causal Inference (DTU 02463 - Active Machine Learning and Agency)
EddieCunningham/CausalInference
Fast inference for Bayesian Networks
mohelm/causalipy
Causal inference methods implemented in Python.
goncalorafaria/causaldiscovery-latent-interventions
Method based on neural networks and variational inference for causal discovery under latent interventions, i. e. learning a shared causal graph among a infinite mixture (under a Dirichlet process prior) of intervention structural causal models .
NorthGuard/IntroductionToCausalInference
A free and friendly introduction to causal inference with few prerequisites.
amazon-science/azcausal
Causal Inference in Python
huckiyang/Obs-Causal-Q-Network
AAAI 22 - Training a Resilient Q-Network against Observational Interference, Causal Inference Q-Networks
mattzheng/causal_inference_demo
Causal Inference Demo
chritoth/active-bayesian-causal-inference
Active Bayesian Causal Inference (Neurips'22)
amzn/credence-to-causal-estimation
A framework for generating complex and realistic datasets for use in evaluating causal inference methods.
andrewtavis/causeinfer
Machine learning based causal inference/uplift in Python
facebookresearch/CausalSkillLearning
Codebase for project about unsupervised skill learning via variational inference and causality.