A new method for detecting gene-expression patterns linked to lineage progression, providing a powerful tool for studying cell state memory across biological systems.
Algorithms and AI for a better world
Assistant Professor Manish Raghavan wants computational techniques to help solve societal problems.
How hard is it to prevent recurring blackouts in Puerto Rico?
Using the island as a model, researchers demonstrate the “DyMonDS” framework can improve resiliency to extreme weather and ease the integration of new resources.
A new technique identifies and removes the training examples that contribute most to a machine-learning model’s failures.
Beery, Farina, Ghassemi, Kim named AI2050 Early Career Fellows
The new crop of AI2050 Early Career Fellows was announced Dec. 10th.
The technique could make AI systems better at complex tasks that involve variability.
Improving health, one machine learning system at a time
Marzyeh Ghassemi works to ensure health-care models are trained to be robust and fair.
A causal theory for studying the cause-and-effect relationships of genes
By sidestepping the need for costly interventions, a new method could potentially reveal gene regulatory programs, paving the way for targeted treatments.
Despite its impressive output, generative AI doesn’t have a coherent understanding of the world
Researchers show that even the best-performing large language models don’t form a true model of the world and its rules, and can thus fail unexpectedly on similar tasks.
Researchers find large language models make inconsistent decisions about whether to call the police when analyzing surveillance videos.