Jake Snell

4 papers and 82 indexed citations .

Jake Snell is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Computational Theory and Mathematics. According to data from OpenAlex, Jake Snell has authored 4 papers receiving a total of 82 indexed citations (citations by other indexed papers that have themselves been cited), including 3 papers in Artificial Intelligence, 2 papers in Computer Vision and Pattern Recognition and 1 paper in Computational Theory and Mathematics. Recurrent topics in Jake Snell’s work include Generative Adversarial Networks and Image Synthesis (2 papers), Machine Learning and Data Classification (1 paper) and Statistical and Computational Modeling (1 paper). Jake Snell is often cited by papers focused on Generative Adversarial Networks and Image Synthesis (2 papers), Machine Learning and Data Classification (1 paper) and Statistical and Computational Modeling (1 paper). Jake Snell collaborates with scholars based in Canada and United States. Jake Snell's co-authors include Richard S. Zemel, Renjie Liao, Marc T. Law, Eleni Triantafillou, Hugo Larochelle, Josh Tenenbaum, Kevin Swersky, Sachin Ravi, Mengye Ren and Raquel Urtasun and has published in prestigious journals such as arXiv (Cornell University), International Conference on Machine Learning and International Conference on Learning Representations.