81 citations · 202 across the 38 of their papers we have counts for
6 papers · 1 filter
AI-Bind: Improving Binding Predictions for Novel Protein Targets and Ligands
Ayan Chatterjee, Robin Walters, Zohair Shafi +7
Identifying novel drug-target interactions (DTI) is a critical and rate limiting step in drug discovery. While deep learning models have been proposed to accelerate the identificat…
Automatic Symmetry Discovery with Lie Algebra Convolutional Network
Nima Dehmamy, Robin Walters, Yanchen Liu +2
Existing equivariant neural networks require prior knowledge of the symmetry group and discretization for continuous groups. We propose to work with Lie algebras (infinitesimal gen…
Equivariant Learning in Spatial Action Spaces
Dian Wang, Robin Walters, Xupeng Zhu +1
Recently, a variety of new equivariant neural network model architectures have been proposed that generalize better over rotational and reflectional symmetries than standard models…
Universal approximation and model compression for radial neural networks
Iordan Ganev, Twan van Laarhoven, Robin Walters
We introduce a class of fully-connected neural networks whose activation functions, rather than being pointwise, rescale feature vectors by a function depending only on their norm.…
Traffic Forecasting using Vehicle-to-Vehicle Communication
Steven Wong, Lejun Jiang, Robin Walters +3
We take the first step in using vehicle-to-vehicle (V2V) communication to provide real-time on-board traffic predictions. In order to best utilize real-world V2V communication data…
Meta-Learning Dynamics Forecasting Using Task Inference
Rui Wang, Robin Walters, Rose Yu
Current deep learning models for dynamics forecasting struggle with generalization. They can only forecast in a specific domain and fail when applied to systems with different para…