1 citations · 1 across the 4 of their papers we have counts for
11 papers
OmniLayout: Room Layout Reconstruction from Indoor Spherical Panoramas
Shivansh Rao, Vikas Kumar, Daniel Kifer +2
Given a single RGB panorama, the goal of 3D layout reconstruction is to estimate the room layout by predicting the corners, floor boundary, and ceiling boundary. A common approach…
Recognizing and Verifying Mathematical Equations using Multiplicative Differential Neural Units
Ankur Mali, Alexander Ororbia, Daniel Kifer +1
Automated mathematical reasoning is a challenging problem that requires an agent to learn algebraic patterns that contain long-range dependencies. Two particular tasks that test th…
Recognizing Long Grammatical Sequences Using Recurrent Networks Augmented With An External Differentiable Stack
Ankur Mali, Alexander Ororbia, Daniel Kifer +1
Recurrent neural networks (RNNs) are a widely used deep architecture for sequence modeling, generation, and prediction. Despite success in applications such as machine translation…
Large-Scale Gradient-Free Deep Learning with Recursive Local Representation Alignment
Alexander Ororbia, Ankur Mali, Daniel Kifer +1
Training deep neural networks on large-scale datasets requires significant hardware resources whose costs (even on cloud platforms) put them out of reach of smaller organizations,…
Sibling Neural Estimators: Improving Iterative Image Decoding with Gradient Communication
Ankur Mali, Alexander G. Ororbia, Clyde Lee Giles
For lossy image compression, we develop a neural-based system which learns a nonlinear estimator for decoding from quantized representations. The system links two recurrent network…
The Neural State Pushdown Automata
Ankur Mali, Alexander Ororbia, C. Lee Giles
In order to learn complex grammars, recurrent neural networks (RNNs) require sufficient computational resources to ensure correct grammar recognition. A widely-used approach to exp…