
LaTeq: Converting equation images to LaTeX
Under supervision of Frank Wood
We trained a generative model for LaTeX equation codes, which will be used as a part of a probabilistic program to perform Bayesian inference for converting equation images to LaTeX codes.


A bayesian approach to Visual Question Answering
Gursimran Singh, Saeid Naderiparizi, Setareh Cohan
Probabilistic Programming course, 2018
Using probabilistic programming and inference compilation to solve visual question answering task.


RegNet: Regularizing Deep Networks
(code)
Setareh Cohan, Saeid Naderiparizi
Multimodal Learning with Vision, Language and Sound course, 2018
We can define regularizers to improve model's performance in the case of not having enough data for few classes.
We tried different regularizers and tested it on image classification task.


A MultiPlane BlockCoordinate FrankWolfe Algorithm for Training Latent Structural SVMs
Under supervision of Christoph H. Lampert
We designed and implemented a method for training Latent Structural SVMs with costly maxoracles using FrankWolfe algorithm on the dual objective. The method does not need specifying a learning rate and it gives a definite result.


Sequential Bound Optimization
Under supervision of Sobhan Naderi Parizi
We proposed an iterative procedure for optimizing nonconvex objective functions that works by optimizing a sequence of convex bounds on the true objective.


Learning to ride a bike
(code)
Setareh Cohan, Saeid Naderiparizi
Computer Animation course, 2017
We implemented a simulator for bicycle motion and used Fitted Value Iteration algorithm for learning to keep the bike balanced. The next goal is to add a target point which the bike should learn to get there and meanwhile, keep the bike balanced.


Learning Influence Probabilities under ICIDT model
(code)
Saeid Naderiparizi, Polina Zablotskaia, Setareh Cohan
Topics in Data Management  Social and Information Networks course, 2017
We came up with a model for influence propagation in social networks which captures decay in adoption probabilities over time and implemented maximum likelihood estimation in C++ to learn the probabilities under this model. To my knowledge, the problem of learning probabilities in this time decaying model had not been studied before.


Implementation of a 3D reconstruction system
Saeid Naderiparizi, Setareh Cohan
Fundamentals of 3D Computer Vision course, 2016
Implemented an algortithm to generate the point cloud of a 3D object using a few photos taken of it. It uses SURF features to find and match keypoints, find position of cameras and then aggregates them to generate the point cloud. This project is done in Matlab.


Implemetation of Bitonic Sort in CUDA for NVIDIA GPUs
Fundamentals of Multicore Computing course, 2015
Implemented Bitonic Sort in CUDA and parallelized it according to the NVIDIA architecture to maximize performance.

