161 citations · 221 across the 15 of their papers we have counts for
33 papers
Transfer Learning with Kernel Methods
Adityanarayanan Radhakrishnan, Max Ruiz Luyten, Neha Prasad +1
Transfer learning refers to the process of adapting a model trained on a source task to a target task. While kernel methods are conceptually and computationally simple machine lear…
Matching a Desired Causal State via Shift Interventions
Jiaqi Zhang, Chandler Squires, Caroline Uhler
Transforming a causal system from a given initial state to a desired target state is an important task permeating multiple fields including control theory, biology, and materials s…
A Mechanism for Producing Aligned Latent Spaces with Autoencoders
Saachi Jain, Adityanarayanan Radhakrishnan, Caroline Uhler
Aligned latent spaces, where meaningful semantic shifts in the input space correspond to a translation in the embedding space, play an important role in the success of downstream t…
Identifying 3D Genome Organization in Diploid Organisms via Euclidean Distance Geometry
Anastasiya Belyaeva, Kaie Kubjas, Lawrence J. Sun +1
The spatial organization of the DNA in the cell nucleus plays an important role for gene regulation, DNA replication, and genomic integrity. Through the development of chromosome c…
Efficient Permutation Discovery in Causal DAGs
Chandler Squires, Joshua Amaniampong, Caroline Uhler
The problem of learning a directed acyclic graph (DAG) up to Markov equivalence is equivalent to the problem of finding a permutation of the variables that induces the sparsest gra…
Joint Inference of Multiple Graphs from Matrix Polynomials
Madeline Navarro, Yuhao Wang, Antonio G. Marques +2
Inferring graph structure from observations on the nodes is an important and popular network science task. Departing from the more common inference of a single graph and motivated…