no code implementations • 21 Dec 2023 • Sean Memery, Mirella Lapata, Kartic Subr
Several machine learning methods aim to learn or reason about complex physical systems.
1 code implementation • 19 Jun 2023 • Sean Memery, Osmar Cedron, Kartic Subr
Since the output of our model is a parametric BRDF, rather than an image of the material, it may be used to render materials using any shape under arbitrarily specified viewing and lighting conditions.
1 code implementation • 28 Oct 2021 • Alexandros Dimitrios Keros, Vidit Nanda, Kartic Subr
Simplicial complexes can be viewed as high dimensional generalizations of graphs that explicitly encode multi-way ordered relations between vertices at different resolutions, all at once.
no code implementations • 16 Sep 2021 • Leonardo V. Castorina, Rokas Petrenas, Kartic Subr, Christopher W. Wood
We compare five existing models with two novel models for sequence prediction.
no code implementations • 30 Nov 2020 • Tatiana Lopez-Guevara, Michael Burke, Nicholas K. Taylor, Kartic Subr
This distribution can then be used as a policy certificate in downstream applications.
1 code implementation • 3 Aug 2020 • Michael Burke, Kartic Subr, Subramanian Ramamoorthy
Humans can easily reason about the sequence of high level actions needed to complete tasks, but it is particularly difficult to instil this ability in robots trained from relatively few examples.
no code implementations • 25 Jun 2020 • Kartic Subr
The use of a \emph{proxy} or surrogate for the true function is useful if repeated evaluations are necessary.
no code implementations • 17 Jun 2020 • Rita Pucci, Jitendra Shankaraiah, Devcharan Jathanna, Ullas Karanth, Kartic Subr
We develop automatic algorithms that are able to detect animals, identify the species of animals and to recognize individual animals for two species.
no code implementations • 4 Feb 2020 • Michael Burke, Katie Lu, Daniel Angelov, Artūras Straižys, Craig Innes, Kartic Subr, Subramanian Ramamoorthy
This work considers the inverse problem, where the goal of the task is unknown, and a reward function needs to be inferred from exploratory example demonstrations provided by a demonstrator, for use in a downstream informative path-planning policy.
no code implementations • 29 Nov 2017 • Paul Henderson, Kartic Subr, Vittorio Ferrari
Efficient authoring of vast virtual environments hinges on algorithms that are able to automatically generate content while also being controllable.
no code implementations • CVPR 2013 • Neill D. F. Campbell, Kartic Subr, Jan Kautz
Conditional Random Fields (CRFs) are used for diverse tasks, ranging from image denoising to object recognition.