2 citations · 3 across the 6 of their papers we have counts for
6 papers
Unifying Theories in High-Dimensional Biology: Approaches, Challenges and Opportunities
Marianne Bauer, Akshit Goyal, Sidhartha Goyal +19
Across biological subdisciplines, the last decade has seen an explosion of high-dimensional datasets, including datasets for cells, species, immune systems, neurons and behaviour.…
Identifying nonequilibrium degrees of freedom in high-dimensional stochastic systems
Catherine Ji, Ravin Raj, Benjamin Eysenbach +1
Any coarse-grained description of a nonequilibrium system should faithfully represent its latent irreversible degrees of freedom. However, standard dimensionality reduction methods…
In-Context Learning Strategies Emerge Rationally
Daniel Wurgaft, Ekdeep Singh Lubana, Core Francisco Park +3
Recent work analyzing in-context learning (ICL) has identified a broad set of strategies that describe model behavior in different experimental conditions. We aim to unify these fi…
Inferring genotype-phenotype maps using attention models
Krishna Rijal, Caroline M. Holmes, Samantha Petti +3
Predicting phenotype from genotype is a central challenge in genetics. Traditional approaches in quantitative genetics typically analyze this problem using methods based on linear…
Differential learning kinetics govern the transition from memorization to generalization during in-context learning
Alex Nguyen, Gautam Reddy
Transformers exhibit in-context learning (ICL): the ability to use novel information presented in the context without additional weight updates. Recent work shows that ICL emerges…
The mechanistic basis of data dependence and abrupt learning in an in-context classification task
Gautam Reddy
Transformer models exhibit in-context learning: the ability to accurately predict the response to a novel query based on illustrative examples in the input sequence. In-context lea…