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09/09/2023
Neural Latent Geometry Search: Product Manifold Inference via Gromov-Hausdorff-Informed Bayesian Optimization
Recent research indicates that the performance of machine learning model...
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09/09/2023
Gromov-Hausdorff Distances for Comparing Product Manifolds of Model Spaces
Recent studies propose enhancing machine learning models by aligning the...
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06/27/2023
AutoGraph: Predicting Lane Graphs from Traffic Observations
Lane graph estimation is a long-standing problem in the context of auton...
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06/15/2023
Reward-Free Curricula for Training Robust World Models
There has been a recent surge of interest in developing generally-capabl...
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05/22/2023
You Only Look at One: Category-Level Object Representations for Pose Estimation From a Single Example
In order to meaningfully interact with the world, robot manipulators mus...
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05/16/2023
RAMP: A Benchmark for Evaluating Robotic Assembly Manipulation and Planning
We introduce RAMP, an open-source robotics benchmark inspired by real-wo...
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03/21/2023
Projections of Model Spaces for Latent Graph Inference
Graph Neural Networks leverage the connectivity structure of graphs as a...
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03/06/2023
Efficient Skill Acquisition for Complex Manipulation Tasks in Obstructed Environments
Data efficiency in robotic skill acquisition is crucial for operating ro...
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03/06/2023
Leveraging Scene Embeddings for Gradient-Based Motion Planning in Latent Space
Motion planning framed as optimisation in structured latent spaces has r...
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02/06/2023
DITTO: Offline Imitation Learning with World Models
We propose DITTO, an offline imitation learning algorithm which uses wor...
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10/21/2022
Reaching Through Latent Space: From Joint Statistics to Path Planning in Manipulation
We present a novel approach to path planning for robotic manipulators, i...
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06/22/2022
Variational Causal Dynamics: Discovering Modular World Models from Interventions
Latent world models allow agents to reason about complex environments wi...
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06/07/2022
ObPose: Leveraging Canonical Pose for Object-Centric Scene Inference in 3D
We present ObPose, an unsupervised object-centric generative model that ...
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05/02/2022
VAE-Loco: Versatile Quadruped Locomotion by Learning a Disentangled Gait Representation
Quadruped locomotion is rapidly maturing to a degree where robots now ro...
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04/07/2022
Zero-Shot Category-Level Object Pose Estimation
Object pose estimation is an important component of most vision pipeline...
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03/01/2022
Fast-MbyM: Leveraging Translational Invariance of the Fourier Transform for Efficient and Accurate Radar Odometry
Masking By Moving (MByM), provides robust and accurate radar odometry me...
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01/20/2022
Priors, Hierarchy, and Information Asymmetry for Skill Transfer in Reinforcement Learning
The ability to discover behaviours from past experience and transfer the...
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12/09/2021
Next Steps: Learning a Disentangled Gait Representation for Versatile Quadruped Locomotion
Quadruped locomotion is rapidly maturing to a degree where robots now ro...
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11/15/2021
Semantically Grounded Object Matching for Robust Robotic Scene Rearrangement
Object rearrangement has recently emerged as a key competency in robot m...
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10/28/2021
From Machine Learning to Robotics: Challenges and Opportunities for Embodied Intelligence
Machine learning has long since become a keystone technology, accelerati...
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07/05/2021
Universal Approximation of Functions on Sets
Modelling functions of sets, or equivalently, permutation-invariant func...
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05/31/2021
APEX: Unsupervised, Object-Centric Scene Segmentation and Tracking for Robot Manipulation
Recent advances in unsupervised learning for object detection, segmentat...
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05/19/2021
E(n) Equivariant Normalizing Flows for Molecule Generation in 3D
This paper introduces a generative model equivariant to Euclidean symmet...
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04/20/2021
GENESIS-V2: Inferring Unordered Object Representations without Iterative Refinement
Advances in object-centric generative models (OCGMs) have culminated in ...
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03/22/2021
Introspective Visuomotor Control: Exploiting Uncertainty in Deep Visuomotor Control for Failure Recovery
End-to-end visuomotor control is emerging as a compelling solution for r...
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02/26/2021
Iterative SE(3)-Transformers
When manipulating three-dimensional data, it is possible to ensure that ...
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11/29/2020
There and Back Again: Learning to Simulate Radar Data for Real-World Applications
Simulating realistic radar data has the potential to significantly accel...
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07/13/2020
Reconstruction Bottlenecks in Object-Centric Generative Models
A range of methods with suitable inductive biases exist to learn interpr...
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07/03/2020
First Steps: Latent-Space Control with Semantic Constraints for Quadruped Locomotion
Traditional approaches to quadruped control frequently employ simplified...
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07/02/2020
RELATE: Physically Plausible Multi-Object Scene Synthesis Using Structured Latent Spaces
We present RELATE, a model that learns to generate physically plausible ...
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03/19/2020
Goal-Conditioned End-to-End Visuomotor Control for Versatile Skill Primitives
Visuomotor control (VMC) is an effective means of achieving basic manipu...
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03/04/2020
Localising Faster: Efficient and precise lidar-based robot localisation in large-scale environments
This paper proposes a novel approach for global localisation of mobile r...
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01/29/2020
Under the Radar: Learning to Predict Robust Keypoints for Odometry Estimation and Metric Localisation in Radar
This paper presents a self-supervised framework for learning to detect r...
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11/19/2019
Attention Privileged Reinforcement Learning For Domain Transfer
Applying reinforcement learning (RL) to physical systems presents notabl...
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09/30/2019
Imagine That! Leveraging Emergent Affordances for Tool Synthesis in Reaching Tasks
In this paper we investigate an artificial agent's ability to perform ta...
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09/09/2019
Masking by Moving: Learning Distraction-Free Radar Odometry from Pose Information
This paper presents an end-to-end radar odometry system which delivers r...
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09/03/2019
The Oxford Radar RobotCar Dataset: A Radar Extension to the Oxford RobotCar Dataset
In this paper we present The Oxford Radar RobotCar Dataset, a new datase...
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07/30/2019
GENESIS: Generative Scene Inference and Sampling with Object-Centric Latent Representations
Generative models are emerging as promising tools in robotics and reinfo...
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07/12/2019
End-to-end Recurrent Multi-Object Tracking and Trajectory Prediction with Relational Reasoning
The majority of contemporary object-tracking approaches used in autonomo...
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01/25/2019
On the Limitations of Representing Functions on Sets
Recent work on the representation of functions on sets has considered th...
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10/18/2018
Probably Unknown: Deep Inverse Sensor Modelling In Radar
Radar presents a promising alternative to lidar and vision in autonomous...
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09/27/2018
Dropout Distillation for Efficiently Estimating Model Confidence
We propose an efficient way to output better calibrated uncertainty scor...
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06/14/2018
Neural Stethoscopes: Unifying Analytic, Auxiliary and Adversarial Network Probing
Model interpretability and systematic, targeted model adaptation present...
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06/05/2018
Sequential Attend, Infer, Repeat: Generative Modelling of Moving Objects
We present Sequential Attend, Infer, Repeat (SQAIR), an interpretable de...
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04/21/2018
ShapeStacks: Learning Vision-Based Physical Intuition for Generalised Object Stacking
Physical intuition is pivotal for intelligent agents to perform complex ...
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03/02/2018
TACO: Learning Task Decomposition via Temporal Alignment for Control
Many advanced Learning from Demonstration (LfD) methods consider the dec...
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12/20/2017
Incremental Adversarial Domain Adaptation for Continually Changing Environments
Continuous appearance shifts such as changes in weather and lighting con...
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12/20/2017
Incremental Adversarial Domain Adaptation
Continuous appearance shifts such as changes in weather and lighting con...
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11/17/2017
Driven to Distraction: Self-Supervised Distractor Learning for Robust Monocular Visual Odometry in Urban Environments
We present a self-supervised approach to ignoring "distractors" in camer...
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08/07/2017