3 citations · 3 across the 3 of their papers we have counts for
7 papers
Self-Supervised Robust Scene Flow Estimation via the Alignment of Probability Density Functions
Pan He, Patrick Emami, Sanjay Ranka +1
In this paper, we present a new self-supervised scene flow estimation approach for a pair of consecutive point clouds. The key idea of our approach is to represent discrete point c…
Hybrid Generative Models for Two-Dimensional Datasets
Hoda Shajari, Jaemoon Lee, Sanjay Ranka +1
Two-dimensional array-based datasets are pervasive in a variety of domains. Current approaches for generative modeling have typically been limited to conventional image datasets an…
Efficient Iterative Amortized Inference for Learning Symmetric and Disentangled Multi-Object Representations
Patrick Emami, Pan He, Sanjay Ranka +1
Unsupervised multi-object representation learning depends on inductive biases to guide the discovery of object-centric representations that generalize. However, we observe that met…
Domain-guided Machine Learning for Remotely Sensed In-Season Crop Growth Estimation
George Worrall, Anand Rangarajan, Jasmeet Judge
Advanced machine learning techniques have been used in remote sensing (RS) applications such as crop mapping and yield prediction, but remain under-utilized for tracking crop progr…
SparsePipe: Parallel Deep Learning for 3D Point Clouds
Keke Zhai, Pan He, Tania Banerjee +2
We propose SparsePipe, an efficient and asynchronous parallelism approach for handling 3D point clouds with multi-GPU training. SparsePipe is built to support 3D sparse data such a…
A Unified Framework for Multiclass and Multilabel Support Vector Machines
Hoda Shajari, Anand Rangarajan
We propose a novel integrated formulation for multiclass and multilabel support vector machines (SVMs). A number of approaches have been proposed to extend the original binary SVM…