113 citations · 277 across the 15 of their papers we have counts for
18 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…
Learning Scene Dynamics from Point Cloud Sequences
Pan He, Patrick Emami, Sanjay Ranka +1
Understanding 3D scenes is a critical prerequisite for autonomous agents. Recently, LiDAR and other sensors have made large amounts of data available in the form of temporal sequen…
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…
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…
Real-time Intersection Optimization for Signal Phasing, Timing, and Automated Vehicles' Trajectories
Mahmoud Pourmehrab, Lily Elefteriadou, Sanjay Ranka
This study aims to develop a real-time intersection optimization (RIO) control algorithm to efficiently serve traffic of Connected and Automated Vehicles (CAVs) and conventional ve…
Intelligent Intersection: Two-Stream Convolutional Networks for Real-time Near Accident Detection in Traffic Video
Xiaohui Huang, Pan He, Anand Rangarajan +1
In Intelligent Transportation System, real-time systems that monitor and analyze road users become increasingly critical as we march toward the smart city era. Vision-based framewo…
Dynamic Load Balancing for Compressible Multiphase Turbulence
Keke Zhai, Tania Banerjee, David Zwick +2
CMT-nek is a new scientific application for performing high fidelity predictive simulations of particle laden explosively dispersed turbulent flows. CMT-nek involves detailed simul…
Learning Permutations with Sinkhorn Policy Gradient
Patrick Emami, Sanjay Ranka
Many problems at the intersection of combinatorics and computer science require solving for a permutation that optimally matches, ranks, or sorts some data. These problems usually…
Visual Explanations From Deep 3D Convolutional Neural Networks for Alzheimer's Disease Classification
Chengliang Yang, Anand Rangarajan, Sanjay Ranka
We develop three efficient approaches for generating visual explanations from 3D convolutional neural networks (3D-CNNs) for Alzheimer's disease classification. One approach conduc…
Machine Learning Methods for Data Association in Multi-Object Tracking
Patrick Emami, Panos M. Pardalos, Lily Elefteriadou +1
Data association is a key step within the multi-object tracking pipeline that is notoriously challenging due to its combinatorial nature. A popular and general way to formulate dat…
Global Model Interpretation via Recursive Partitioning
Chengliang Yang, Anand Rangarajan, Sanjay Ranka
In this work, we propose a simple but effective method to interpret black-box machine learning models globally. That is, we use a compact binary tree, the interpretation tree, to e…
Optimizing Signalized Intersections Performance under Conventional and Automated Vehicles Traffic
Mahmoud Pourmehrab, Lily Elefteriadou, Sanjay Ranka +1
Automated vehicles, or AVs (i.e. those that have the ability to operate without a driver and can communicate with the infrastructure) may transform the transportation system. This…
Disaggregation of SMAP L3 Brightness Temperatures to 9km using Kernel Machines
Subit Chakrabarti, Tara Bongiovanni, Jasmeet Judge +2
In this study, a machine learning algorithm is used for disaggregation of SMAP brightness temperatures (T) from 36km to 9km. It uses image segmentation to cluster th…
Spatial Scaling of Satellite Soil Moisture using Temporal Correlations and Ensemble Learning
Subit Chakrabarti, Jasmeet Judge, Tara Bongiovanni +2
A novel algorithm is developed to downscale soil moisture (SM), obtained at satellite scales of 10-40 km by utilizing its temporal correlations to historical auxiliary data at fine…
Downscaling Microwave Brightness Temperatures Using Self Regularized Regressive Models
Subit Chakrabarti, Jasmeet Judge, Anand Rangarajan +1
A novel algorithm is proposed to downscale microwave brightness temperatures (), at scales of 10-40 km such as those from the Soil Moisture Active Passive mission to…
Disaggregation of Remotely Sensed Soil Moisture in Heterogeneous Landscapes using Holistic Structure based Models
Subit Chakrabarti, Jasmeet Judge, Anand Rangarajan +1
In this study, a novel machine learning algorithm is presented for disaggregation of satellite soil moisture (SM) based on self-regularized regressive models (SRRM) using high-reso…
Data-driven Co-clustering Model of Internet Usage in Large Mobile Societies
Saeed Moghaddam, Ahmed Helmy, Sanjay Ranka +1
Design and simulation of future mobile networks will center around human interests and behavior. We propose a design paradigm for mobile networks driven by realistic models of user…