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LMRL will be featuring some of the best efforts in biology and machine learning to spur the next generation of data-driven biological problem-solving. An emphasis on interpretable learning of structure and principles will be applied to work on the level of the genome, molecule, cells, and phenotype. The call for abstracts and travel awards has closed; to join the conference, please submit a poster proposal by October 20. We hope you’ll join us!

LRML at NeurIPS will begin at 9:00am on Friday, December 13th, at the Vancouver Convention Center. Talks and discussions by:

Aviv Regev | Anne Carpenter | Alan Asparu-Guzik | Brookes Paige | Casey Greene | Chang Liu | Daphne Koller | Dana Pe’er | Danilo Bzdok | Dan Yamins | David Duvenaud | David Jones | David Reshef | Debora Marks | Djork-Arne Clevert | Eli Van Allen | Joshua Weinstein | Kresten Lindorff-Larsen | Matt Johnson | Matt Kusner | Max Welling | Meromit Singer | Nikolai Slavov | Nir Hacohen | Pam Silver | Possu Huang | Quaid Morris | Rediet Abebe | Samantha Morris | Sara Mostafavi | Scott Linderman | Smita Krishnaswamy | Soumya Raychaudhuri | Suchi Saria | Wouter Boomsma | Yixin Wang | And more to be announced.


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