Lista de obras - Pieter Abbeel - Dominio Público Uruguay

#Exploration: A Study of Count-Based Exploration for Deep Reinforcement Learning ⬇️

artículo científico publicado en 2017

A Geometric Approach to Robotic Laundry Folding1

A Survey of Research on Cloud Robotics and Automation

A biological micro actuator: graded and closed-loop control of insect leg motion by electrical stimulation of muscles

artículo científico publicado en 2014

A geometric approach to robotic laundry folding

A robot path planning framework that learns from experience

article published in 2012

A single-use haptic palpation probe for locating subcutaneous blood vessels in robot-assisted minimally invasive surgery

Active exploration using trajectory optimization for robotic grasping in the presence of occlusions

Addressing Sample Complexity in Visual Tasks Using HER and Hallucinatory GANs ⬇️

An Application of Reinforcement Learning to Aerobatic Helicopter Flight ⬇️

artículo científico publicado en 2007

An algorithm for computing customized 3D printed implants with curvature constrained channels for enhancing intracavitary brachytherapy radiation delivery

scholarly article published August 2013

Apprenticeship learning via inverse reinforcement learning

Automatic Curriculum Learning through Value Disagreement ⬇️

Autonomous multilateral debridement with the Raven surgical robot

AvE: Assistance via Empowerment ⬇️

artículo científico publicado en 2020

Backprop KF: Learning Discriminative Deterministic State Estimators ⬇️

artículo científico publicado en 2016

Combinatorial Energy Learning for Image Segmentation ⬇️

artículo científico publicado en 2016

Compositional Plan Vectors ⬇️

artículo científico publicado en 2019

Compression with Flows via Local Bits-Back Coding ⬇️

Cooperative Inverse Reinforcement Learning ⬇️

artículo científico publicado en 2016

Deciphering the role of a coleopteran steering muscle via free flight stimulation

artículo científico publicado en 2015

Denoising Diffusion Probabilistic Models ⬇️

artículo científico publicado en 2020

End-to-End Training of Deep Visuomotor Policies

artículo científico publicado en 2016

Evaluating Protein Transfer Learning with TAPE ⬇️

artículo científico publicado en 2019

Evolved Policy Gradients ⬇️

GP-GPIS-OPT: Grasp planning with shape uncertainty using Gaussian process implicit surfaces and Sequential Convex Programming

Gaussian belief space planning with discontinuities in sensing domains

Generalized Hindsight for Reinforcement Learning ⬇️

scholarly article by Alexander Li et al published November 2020 in Advances in Neural Information Processing Systems 33

Geometry-Aware Neural Rendering ⬇️

Goal-conditioned Imitation Learning ⬇️

artículo científico publicado en 2019

Gradient Estimation Using Stochastic Computation Graphs ⬇️

Gravity-Based Robotic Cloth Folding

scholarly article by Jur van den Berg et al published 2010 in Springer tracts in advanced robotics

Guided Meta-Policy Search ⬇️

Hierarchical Apprenticeship Learning with Application to Quadruped Locomotion ⬇️

artículo científico publicado en 2008

Hindsight Experience Replay ⬇️

artículo científico publicado en 2017

InfoGAN: Interpretable Representation Learning by Information Maximizing Generative Adversarial Nets ⬇️

artículo científico publicado en 2016

Insect-machine hybrid system

artículo científico publicado en 2013

Inverse Reward Design ⬇️

artículo científico publicado en 2017

LQG-Based Planning, Sensing, and Control of Steerable Needles

article published in 2010

LQG-MP: Optimized path planning for robots with motion uncertainty and imperfect state information

Learning Neural Network Policies with Guided Policy Search under Unknown Dynamics ⬇️

artículo científico publicado en 2014

Learning Plannable Representations with Causal InfoGAN ⬇️

Learning accurate kinematic control of cable-driven surgical robots using data cleaning and Gaussian Process Regression

Learning by observation for surgical subtasks: Multilateral cutting of 3D viscoelastic and 2D Orthotropic Tissue Phantoms

Learning first-order Markov models for control ⬇️

Learning to Poke by Poking: Experiential Learning of Intuitive Physics ⬇️

artículo científico publicado en 2016

Learning vehicular dynamics, with application to modeling helicopters ⬇️

artículo científico publicado en 2006

Link Prediction in Relational Data ⬇️

artículo científico publicado en 2004

MCP: Learning Composable Hierarchical Control with Multiplicative Compositional Policies ⬇️

Managing extreme AI risks amid rapid progress

artículo científico publicado en 2024

Max-margin classification of incomplete data ⬇️

artículo científico publicado en 2007

Meta-Reinforcement Learning of Structured Exploration Strategies ⬇️

scholarly article by Abhishek Gupta et al published 2018 in Advances in Neural Information Processing Systems 31

Motion planning with sequential convex optimization and convex collision checking

Multi-Agent Actor-Critic for Mixed Cooperative-Competitive Environments ⬇️

artículo científico publicado en 2017

Multi-armed bandit models for 2D grasp planning with uncertainty

On a Connection between Importance Sampling and the Likelihood Ratio Policy Gradient ⬇️

artículo científico publicado en 2010

On the Utility of Learning about Humans for Human-AI Coordination ⬇️

One-Shot Imitation Learning ⬇️

artículo científico publicado en 2017

Planning Curvature and Torsion Constrained Ribbons in 3D With Application to Intracavitary Brachytherapy

article by Sachin Patil et al published October 2015 in IEEE Transactions on Automation Science and Engineering

Planning Curvature and Torsion Constrained Ribbons in 3D with Application to Intracavitary Brachytherapy

article by Sachin Patil et al published 2015 in Springer tracts in advanced robotics

Planning locally optimal, curvature-constrained trajectories in 3D using sequential convex optimization

scholarly article published May 2014

Reinforcement Learning with Augmented Data ⬇️

artículo científico publicado en 2020

Risk Aversion in Markov Decision Processes via Near Optimal Chernoff Bounds ⬇️

artículo científico publicado en 2012

Scaling up Gaussian Belief Space Planning Through Covariance-Free Trajectory Optimization and Automatic Differentiation

Sigma hulls for Gaussian belief space planning for imprecise articulated robots amid obstacles

Sparse Graphical Memory for Robust Planning ⬇️

artículo científico publicado en 2020

Stochastic Latent Actor-Critic: Deep Reinforcement Learning with a Latent Variable Model ⬇️

artículo científico publicado en 2020

Superhuman performance of surgical tasks by robots using iterative learning from human-guided demonstrations

The Importance of Sampling in Meta-Reinforcement Learning ⬇️

scholarly article by Bradly Stadie et al published 2018 in Advances in Neural Information Processing Systems 31

The Off-Switch Game

Trajectory-wise Multiple Choice Learning for Dynamics Generalization in Reinforcement Learning ⬇️

artículo científico publicado en 2020

VIME: Variational Information Maximizing Exploration ⬇️

artículo científico publicado en 2016

Value Iteration Networks

scholarly article

Lista de obras de Pieter Abbeel

#Exploration: A Study of Count-Based Exploration for Deep Reinforcement Learning ⬇️

A Geometric Approach to Robotic Laundry Folding1

A Survey of Research on Cloud Robotics and Automation

A biological micro actuator: graded and closed-loop control of insect leg motion by electrical stimulation of muscles

A geometric approach to robotic laundry folding

A robot path planning framework that learns from experience

A single-use haptic palpation probe for locating subcutaneous blood vessels in robot-assisted minimally invasive surgery

Active exploration using trajectory optimization for robotic grasping in the presence of occlusions

Addressing Sample Complexity in Visual Tasks Using HER and Hallucinatory GANs ⬇️

An Application of Reinforcement Learning to Aerobatic Helicopter Flight ⬇️

An algorithm for computing customized 3D printed implants with curvature constrained channels for enhancing intracavitary brachytherapy radiation delivery

Apprenticeship learning via inverse reinforcement learning

Automatic Curriculum Learning through Value Disagreement ⬇️

Autonomous multilateral debridement with the Raven surgical robot

AvE: Assistance via Empowerment ⬇️

Backprop KF: Learning Discriminative Deterministic State Estimators ⬇️

Combinatorial Energy Learning for Image Segmentation ⬇️

Compositional Plan Vectors ⬇️

Compression with Flows via Local Bits-Back Coding ⬇️

Cooperative Inverse Reinforcement Learning ⬇️

Deciphering the role of a coleopteran steering muscle via free flight stimulation

Denoising Diffusion Probabilistic Models ⬇️

End-to-End Training of Deep Visuomotor Policies

Evaluating Protein Transfer Learning with TAPE ⬇️

Evolved Policy Gradients ⬇️

GP-GPIS-OPT: Grasp planning with shape uncertainty using Gaussian process implicit surfaces and Sequential Convex Programming

Gaussian belief space planning with discontinuities in sensing domains

Generalized Hindsight for Reinforcement Learning ⬇️

Geometry-Aware Neural Rendering ⬇️

Goal-conditioned Imitation Learning ⬇️

Gradient Estimation Using Stochastic Computation Graphs ⬇️

Gravity-Based Robotic Cloth Folding

Guided Meta-Policy Search ⬇️

Hierarchical Apprenticeship Learning with Application to Quadruped Locomotion ⬇️

Hindsight Experience Replay ⬇️

InfoGAN: Interpretable Representation Learning by Information Maximizing Generative Adversarial Nets ⬇️

Insect-machine hybrid system

Inverse Reward Design ⬇️

LQG-Based Planning, Sensing, and Control of Steerable Needles

LQG-MP: Optimized path planning for robots with motion uncertainty and imperfect state information

Learning Neural Network Policies with Guided Policy Search under Unknown Dynamics ⬇️

Learning Plannable Representations with Causal InfoGAN ⬇️

Learning accurate kinematic control of cable-driven surgical robots using data cleaning and Gaussian Process Regression

Learning by observation for surgical subtasks: Multilateral cutting of 3D viscoelastic and 2D Orthotropic Tissue Phantoms

Learning first-order Markov models for control ⬇️

Learning to Poke by Poking: Experiential Learning of Intuitive Physics ⬇️

Learning vehicular dynamics, with application to modeling helicopters ⬇️

Link Prediction in Relational Data ⬇️

MCP: Learning Composable Hierarchical Control with Multiplicative Compositional Policies ⬇️

Managing extreme AI risks amid rapid progress

Max-margin classification of incomplete data ⬇️

Meta-Reinforcement Learning of Structured Exploration Strategies ⬇️

Motion planning with sequential convex optimization and convex collision checking

Multi-Agent Actor-Critic for Mixed Cooperative-Competitive Environments ⬇️

Multi-armed bandit models for 2D grasp planning with uncertainty

On a Connection between Importance Sampling and the Likelihood Ratio Policy Gradient ⬇️

On the Utility of Learning about Humans for Human-AI Coordination ⬇️

One-Shot Imitation Learning ⬇️

Planning Curvature and Torsion Constrained Ribbons in 3D With Application to Intracavitary Brachytherapy

Planning Curvature and Torsion Constrained Ribbons in 3D with Application to Intracavitary Brachytherapy

Planning locally optimal, curvature-constrained trajectories in 3D using sequential convex optimization

Reinforcement Learning with Augmented Data ⬇️

Risk Aversion in Markov Decision Processes via Near Optimal Chernoff Bounds ⬇️

Scaling up Gaussian Belief Space Planning Through Covariance-Free Trajectory Optimization and Automatic Differentiation

Sigma hulls for Gaussian belief space planning for imprecise articulated robots amid obstacles

Sparse Graphical Memory for Robust Planning ⬇️

Stochastic Latent Actor-Critic: Deep Reinforcement Learning with a Latent Variable Model ⬇️

Superhuman performance of surgical tasks by robots using iterative learning from human-guided demonstrations

The Importance of Sampling in Meta-Reinforcement Learning ⬇️

The Off-Switch Game

Trajectory-wise Multiple Choice Learning for Dynamics Generalization in Reinforcement Learning ⬇️

VIME: Variational Information Maximizing Exploration ⬇️

Value Iteration Networks