2 citations · 4 across the 5 of their papers we have counts for
5 papers
VI3NR: Variance Informed Initialization for Implicit Neural Representations
Chamin Hewa Koneputugodage, Yizhak Ben-Shabat, Sameera Ramasinghe +1
Implicit Neural Representations (INRs) are a versatile and powerful tool for encoding various forms of data, including images, videos, sound, and 3D shapes. A critical factor in th…
Neural Experts: Mixture of Experts for Implicit Neural Representations
Yizhak Ben-Shabat, Chamin Hewa Koneputugodage, Sameera Ramasinghe +1
Implicit neural representations (INRs) have proven effective in various tasks including image, shape, audio, and video reconstruction. These INRs typically learn the implicit field…
Exploiting Problem Structure in Deep Declarative Networks: Two Case Studies
Stephen Gould, Dylan Campbell, Itzik Ben-Shabat +2
Deep declarative networks and other recent related works have shown how to differentiate the solution map of a (continuous) parametrized optimization problem, opening up the possib…
DiGS : Divergence guided shape implicit neural representation for unoriented point clouds
Yizhak Ben-Shabat, Chamin Hewa Koneputugodage, Stephen Gould
Shape implicit neural representations (INRs) have recently shown to be effective in shape analysis and reconstruction tasks. Existing INRs require point coordinates to learn the im…
Computer Assisted Composition in Continuous Time
Chamin Hewa Koneputugodage, Rhys Healy, Sean Lamont +9
We address the problem of combining sequence models of symbolic music with user defined constraints. For typical models this is non-trivial as only the conditional distribution of…