121 citations · 133 across the 5 of their papers we have counts for
5 papers
PopSparse: Accelerated block sparse matrix multiplication on IPU
Zhiyi Li, Douglas Orr, Valeriu Ohan +5
Reducing the computational cost of running large scale neural networks using sparsity has attracted great attention in the deep learning community. While much success has been achi…
GPS++: Reviving the Art of Message Passing for Molecular Property Prediction
Dominic Masters, Josef Dean, Kerstin Klaser +9
We present GPS++, a hybrid Message Passing Neural Network / Graph Transformer model for molecular property prediction. Our model integrates a well-tuned local message passing compo…
GPS++: An Optimised Hybrid MPNN/Transformer for Molecular Property Prediction
Dominic Masters, Josef Dean, Kerstin Klaser +7
This technical report presents GPS++, the first-place solution to the Open Graph Benchmark Large-Scale Challenge (OGB-LSC 2022) for the PCQM4Mv2 molecular property prediction task.…
Monocular Differentiable Rendering for Self-Supervised 3D Object Detection
Deniz Beker, Hiroharu Kato, Mihai Adrian Morariu +4
3D object detection from monocular images is an ill-posed problem due to the projective entanglement of depth and scale. To overcome this ambiguity, we present a novel self-supervi…
Differentiable Rendering: A Survey
Hiroharu Kato, Deniz Beker, Mihai Morariu +4
Deep neural networks (DNNs) have shown remarkable performance improvements on vision-related tasks such as object detection or image segmentation. Despite their success, they gener…