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Moksh Jain. PhD Student in Machine Learning at Mila and UdeM.
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Moksh Jain Toggle navigation about (current) blog publications cv Moksh Jain I am a Ph.D. student at Mila and Université de Montréal supervised by Yoshua Bengio . I am interested in developing machine learning algorithms for effective experimental design, incorporating tools from probabilistic inference and modern deep learning. My work focuses on the probabilistic inference framework of GFlowNets. I am interested in applications of these algorithms to accelerate the scientific discovery process. At Mila, I lead various efforts to develop novel machine learning approaches in the context of drug discovery. I was a research intern with Jason Hartford at Valence Labs (@ Recursion ) working on experimental design for gene knockout experiments. Before joining Mila as a graduate student, I was a visiting researcher working with Yoshua Bengio on uncertainty estimation and drug discovery. I also spent a year at Microsoft Turing working on compressing and optimizi...
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