
-
Learning Intuitive Physics with Multimodal Generative Models
Predicting the future interaction of objects when they come into contact...
read it
-
Intervention Design for Effective Sim2Real Transfer
The goal of this work is to address the recent success of domain randomi...
read it
-
Multimodal dynamics modeling for off-road autonomous vehicles
Dynamics modeling in outdoor and unstructured environments is difficult ...
read it
-
Seeing Through your Skin: Recognizing Objects with a Novel Visuotactile Sensor
We introduce a new class of vision-based sensor and associated algorithm...
read it
-
Learning the Latent Space of Robot Dynamics for Cutting Interaction Inference
Utilization of latent space to capture a lower-dimensional representatio...
read it
-
An Equivalence between Loss Functions and Non-Uniform Sampling in Experience Replay
Prioritized Experience Replay (PER) is a deep reinforcement learning tec...
read it
-
3D Shape Reconstruction from Vision and Touch
When a toddler is presented a new toy, their instinctual behaviour is to...
read it
-
Vision-Based Goal-Conditioned Policies for Underwater Navigation in the Presence of Obstacles
We present Nav2Goal, a data-efficient and end-to-end learning method for...
read it
-
Learning to Drive Off Road on Smooth Terrain in Unstructured Environments Using an On-Board Camera and Sparse Aerial Images
We present a method for learning to drive on smooth terrain while simult...
read it
-
Detecting GAN generated errors
Despite an impressive performance from the latest GAN for generating hyp...
read it
-
Unifying Variational Inference and PAC-Bayes for Supervised Learning that Scales
Neural Network based controllers hold enormous potential to learn comple...
read it
-
Deep learning for Aerosol Forecasting
Reanalysis datasets combining numerical physics models and limited obser...
read it
-
Cascaded Gaussian Processes for Data-efficient Robot Dynamics Learning
Motivated by the recursive Newton-Euler formulation, we propose a novel ...
read it
-
Learning Domain Randomization Distributions for Transfer of Locomotion Policies
Domain randomization (DR) is a successful technique for learning robust ...
read it
-
Human Motion Prediction via Pattern Completion in Latent Representation Space
Inspired by ideas in cognitive science, we propose a novel and general a...
read it
-
Uncertainty Aware Learning from Demonstrations in Multiple Contexts using Bayesian Neural Networks
Diversity of environments is a key challenge that causes learned robotic...
read it
-
GEOMetrics: Exploiting Geometric Structure for Graph-Encoded Objects
Mesh models are a promising approach for encoding the structure of 3D ob...
read it
-
Off-Policy Deep Reinforcement Learning without Exploration
Reinforcement learning traditionally considers the task of balancing exp...
read it
-
Synthesizing Neural Network Controllers with Probabilistic Model based Reinforcement Learning
We present an algorithm for rapidly learning controllers for robotics sy...
read it
-
3D Object Super-Resolution
We consider the problem of scaling deep generative shape models to high-...
read it
-
Cost Adaptation for Robust Decentralized Swarm Behaviour
The multi-agent swarm system is a robust paradigm which can drive effici...
read it
-
Deep Reinforcement Learning that Matters
In recent years, significant progress has been made in solving challengi...
read it
-
Benchmark Environments for Multitask Learning in Continuous Domains
As demand drives systems to generalize to various domains and problems, ...
read it
-
Improved Adversarial Systems for 3D Object Generation and Reconstruction
This paper describes a new approach for training generative adversarial ...
read it
-
Semantic Robot Vision Challenge: Current State and Future Directions
The Semantic Robot Vision Competition provided an excellent opportunity ...
read it