35 citations · 96 across the 16 of their papers we have counts for
4 papers · 1 filter
Dense Uncertainty Estimation
Jing Zhang, Yuchao Dai, Mochu Xiang +7
Deep neural networks can be roughly divided into deterministic neural networks and stochastic neural networks.The former is usually trained to achieve a mapping from input space to…
Conditional Generative Modeling via Learning the Latent Space
Sameera Ramasinghe, Kanchana Ranasinghe, Salman Khan +2
Although deep learning has achieved appealing results on several machine learning tasks, most of the models are deterministic at inference, limiting their application to single-mod…
Blended Convolution and Synthesis for Efficient Discrimination of 3D Shapes
Sameera Ramasinghe, Salman Khan, Nick Barnes +1
Existing networks directly learn feature representations on 3D point clouds for shape analysis. We argue that 3D point clouds are highly redundant and hold irregular (permutation-i…
Volumetric Convolution: Automatic Representation Learning in Unit Ball
Sameera Ramasinghe, Salman Khan, Nick Barnes
Convolution is an efficient technique to obtain abstract feature representations using hierarchical layers in deep networks. Although performing convolution in Euclidean geometries…