research
∙
12/20/2022
Efficient and Sound Differentiable Programming in a Functional Array-Processing Language
Automatic differentiation (AD) is a technique for computing the derivati...
share
research
∙
11/22/2022
BESS: Balanced Entity Sampling and Sharing for Large-Scale Knowledge Graph Completion
We present the award-winning submission to the WikiKG90Mv2 track of OGB-...
research
∙
03/11/2022
FLAG: Flow-based 3D Avatar Generation from Sparse Observations
To represent people in mixed reality applications for collaboration and ...
research
∙
05/06/2021
Hashing Modulo Alpha-Equivalence
In many applications one wants to identify identical subtrees of a progr...
research
∙
07/21/2020
Who Left the Dogs Out? 3D Animal Reconstruction with Expectation Maximization in the Loop
We introduce an automatic, end-to-end method for recovering the 3D pose ...
research
∙
02/28/2020
Inverse Graphics GAN: Learning to Generate 3D Shapes from Unstructured 2D Data
Recent work has shown the ability to learn generative models for 3D shap...
research
∙
11/14/2018
Creatures great and SMAL: Recovering the shape and motion of animals from video
We present a system to recover the 3D shape and motion of a wide variety...
research
∙
07/26/2018
A Benchmark of Selected Algorithmic Differentiation Tools on Some Problems in Computer Vision and Machine Learning
Algorithmic differentiation (AD) allows exact computation of derivatives...
research
∙
06/06/2018
Efficient Differentiable Programming in a Functional Array-Processing Language
We present a system for the automatic differentiation of a higher-order ...
research
∙
02/11/2018
QRkit: Sparse, Composable QR Decompositions for Efficient and Stable Solutions to Problems in Computer Vision
Embedded computer vision applications increasingly require the speed and...
research
∙
11/30/2017
Hybrid VAE: Improving Deep Generative Models using Partial Observations
Deep neural network models trained on large labeled datasets are the sta...
research
∙
08/04/2017
