Robin Walters | DeepAI

DeepAI

Featured Co-authors

Rui Wang
176 publications
Jan-Willem van de Meent
42 publications
Bo Zhao
42 publications
Robert Platt
37 publications
Rose Yu
34 publications
Tina Eliassi-Rad
18 publications
Lawson L. S. Wong
15 publications
Dashun Wang
14 publications
Dian Wang
13 publications
Gabor Orosz
12 publications
Tamás G. Molnár
12 publications

∙ 11/16/2022

The Surprising Effectiveness of Equivariant Models in Domains with Latent Symmetry

Extensive work has demonstrated that equivariant neural networks can sig...

Dian Wang, et al. ∙

∙ 10/31/2022

SEIL: Simulation-augmented Equivariant Imitation Learning

In robotic manipulation, acquiring samples is extremely expensive becaus...

Mingxi Jia, et al. ∙

∙ 10/31/2022

Edge Grasp Network: A Graph-Based SE(3)-invariant Approach to Grasp Detection

Given point cloud input, the problem of 6-DoF grasp pose detection is to...

Haojie Huang, et al. ∙

∙ 08/24/2022

Secondary Protein Structure Prediction Using Neural Networks

In this paper we experiment with using neural network structures to pred...

Sidharth Malhotra, et al. ∙

∙ 07/26/2022

Quiver neural networks

We develop a uniform theoretical approach towards the analysis of variou...

Iordan Ganev, et al. ∙

∙ 07/18/2022

I2I: Image to Icosahedral Projection for SO(3) Object Reasoning from Single-View Images

Reasoning about 3D objects based on 2D images is challenging due to larg...

David Klee, et al. ∙

∙ 06/08/2022

Integrating Symmetry into Differentiable Planning

We study how group symmetry helps improve data efficiency and generaliza...

Linfeng Zhao, et al. ∙

∙ 05/21/2022

Symmetry Teleportation for Accelerated Optimization

Existing gradient-based optimization methods update the parameters local...

Bo Zhao, et al. ∙

∙ 05/04/2022

Probabilistic Symmetry for Improved Trajectory Forecasting

Trajectory prediction is a core AI problem with broad applications in ro...

Sophia Sun, et al. ∙

∙ 04/28/2022

Toward Compositional Generalization in Object-Oriented World Modeling

Compositional generalization is a critical ability in learning and decis...

Linfeng Zhao, et al. ∙

∙ 04/24/2022

Learning Symmetric Embeddings for Equivariant World Models

Incorporating symmetries can lead to highly data-efficient and generaliz...

Jung Yeon Park, et al. ∙

∙ 03/09/2022

On-Robot Policy Learning with O(2)-Equivariant SAC

Recently, equivariant neural network models have been shown to be useful...

Dian Wang, et al. ∙

∙ 03/08/2022

SO(2)-Equivariant Reinforcement Learning

Equivariant neural networks enforce symmetry within the structure of the...

Dian Wang, et al. ∙

∙ 02/18/2022

Sample Efficient Grasp Learning Using Equivariant Models

In planar grasp detection, the goal is to learn a function from an image...

Xupeng Zhu, et al. ∙

∙ 12/25/2021

AI-Bind: Improving Binding Predictions for Novel Protein Targets and Ligands

Identifying novel drug-target interactions (DTI) is a critical and rate ...

Ayan Chatterjee, et al. ∙

∙ 10/28/2021

Equivariant Q Learning in Spatial Action Spaces

Recently, a variety of new equivariant neural network model architecture...

Dian Wang, et al. ∙

∙ 09/15/2021

Automatic Symmetry Discovery with Lie Algebra Convolutional Network

Existing equivariant neural networks for continuous groups require discr...

Nima Dehmamy, et al. ∙

∙ 07/06/2021

The QR decomposition for radial neural networks

We provide a theoretical framework for neural networks in terms of the r...

Iordan Ganev, et al. ∙

∙ 04/12/2021

Traffic Forecasting using Vehicle-to-Vehicle Communication

We take the first step in using vehicle-to-vehicle (V2V) communication t...

Steven Wong, et al. ∙

∙ 02/20/2021

Meta-Learning Dynamics Forecasting Using Task Inference

Current deep learning models for dynamics forecasting struggle with gene...

Rui Wang, et al. ∙

∙ 10/21/2020

Trajectory Prediction using Equivariant Continuous Convolution

Trajectory prediction is a critical part of many AI applications, for ex...

Robin Walters, et al. ∙

∙ 02/08/2020

Incorporating Symmetry into Deep Dynamics Models for Improved Generalization

Training machine learning models that can learn complex spatiotemporal d...

Rui Wang, et al. ∙