9 citations · 11 across the 3 of their papers we have counts for
7 papers
Dynamical Deep Generative Latent Modeling of 3D Skeletal Motion
Amirreza Farnoosh, Sarah Ostadabbas
In this paper, we propose a Bayesian switching dynamical model for segmentation of 3D pose data over time that uncovers interpretable patterns in the data and is generative. Our mo…
Deep Switching Auto-Regressive Factorization:Application to Time Series Forecasting
Amirreza Farnoosh, Bahar Azari, Sarah Ostadabbas
We introduce deep switching auto-regressive factorization (DSARF), a deep generative model for spatio-temporal data with the capability to unravel recurring patterns in the data an…
Deep Markov Spatio-Temporal Factorization
Amirreza Farnoosh, Behnaz Rezaei, Eli Zachary Sennesh +6
We introduce deep Markov spatio-temporal factorization (DMSTF), a generative model for dynamical analysis of spatio-temporal data. Like other factor analysis methods, DMSTF approxi…
G-LBM:Generative Low-dimensional Background Model Estimation from Video Sequences
Behnaz Rezaei, Amirreza Farnoosh, Sarah Ostadabbas
In this paper, we propose a computationally tractable and theoretically supported non-linear low-dimensional generative model to represent real-world data in the presence of noise…
Development of Use-specific High Performance Cyber-Nanomaterial Optical Detectors by Effective Choice of Machine Learning Algorithms
Davoud Hejazi, Shuangjun Liu, Amirreza Farnoosh +2
Due to their inherent variabilities,nanomaterial-based sensors are challenging to translate into real-world applications,where reliability/reproducibility is key.Recently we showed…
DeepPBM: Deep Probabilistic Background Model Estimation from Video Sequences
Amirreza Farnoosh, Behnaz Rezaei, Sarah Ostadabbas
This paper presents a novel unsupervised probabilistic model estimation of visual background in video sequences using a variational autoencoder framework. Due to the redundant natu…