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I am a Ph.D. student in computer science at the University of British Columbia, supervised by Michiel van de Panne. My research goal is to study machine learning for efficient decision making. I am currently interested in learning-based methods for control including reinforcement learning and generative models. Prior to that, I completed my M.Sc. in computer science at the University of British Columbia, supervised by Jim Little and Leonid Sigal. I did my B.Sc. in computer engineering at Sharif University of Technology. |
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Setareh Cohan, Nam Hee Kim, David Rolnick, Michiel van de Panne NeurIPS 2022 [Arxiv][Project Page][Code] |
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Setareh Cohan Ongoing project in which we explore the capabilities of probabilistic diffusion models for human motion synthesis and editing. |
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Gursimran Singh, Saeid Naderiparizi, Setareh Cohan Probabilistic Programming course, winter 2018 [PDF] |
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Setareh Cohan, Saeid Naderiparizi Multimodal Learning with Vision, Language and Sound course, spring 2018 [PDF] [code] |
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Setareh Cohan, Saeid Naderiparizi Machine Learning II course, spring 2018 [PDF] |
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Setareh Cohan, Saeid Naderiparizi Computer Animation course, winter 2017 [PDF] [code] |
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Saeid Naderiparizi, Polina Zablotskaia, Setareh Cohan Social and Information Networks course, winter 2017 [PDF] |
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Setareh Cohan, Saeid Naderiparizi Fundamentals of 3D Computer Vision course, spring 2015 [PDF] |
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Supervisor: Lili Meng Investigated the advantages of integrating probabilistic prediction and selective prediction (or prediction with reject option) for regression tasks. Implemented SelectiveNet (Geifman et al., ICML2019), and altered the prediction modules to probabilistic prediction modules (code is available here). Designed and executed numerical experiments on large computer clusters for classification and regression tasks. |
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Website source from Jon Barron. |