Publications

2020

Causal Network Models of SARS-CoV-2 Expression and Aging to Identify Candidates for Drug Repurposing [arXiv]
Anastasiya Belyaeva*, Louis Cammarata*, Adityanarayanan Radhakrishnan*, Chandler Squires, Karren Dai Yang, G.V. Shivashankar, Caroline Uhler

On Alignment in Deep Linear Neural Networks [arXiv]
Adityanarayanan Radhakrishnan*, Eshaan Nichani*, Daniel Bernstein, Caroline Uhler

2019

Overparameterized Autoencoders can Implement Associative Memory [arXiv]
Adityanarayanan Radhakrishnan, Mikhail Belkin, Caroline Uhler

Memorization in Overparameterized Autoencoders [arXiv, openreview]
Adityanarayanan Radhakrishnan, Mikhail Belkin, Caroline Uhler
ICML Workshop on Identifying and Understanding Deep Learning Phenomena.

2018

Patchnet: Interpretable Neural Net- works for Image Classification [arXiv]
Adityanarayanan Radhakrishnan, Charles Durham, Alican Soylemezoglu, Caroline Uhler
NeurIPS Machine Learning for Health (ML4H) Workshop.

Counting Markov equivalence classes for DAG models on trees [arXiv, DOI]
Adityanarayanan Radhakrishnan, Liam Solus, Caroline Uhler
Discrete Applied Mathematics.

2017

Machine Learning for Nuclear Mechano-Morphometric Biomarkers in Cancer Diagnosis [Link]
Adityanarayanan Radhakrishnan, Karthik Damodaran, Alican Soylemezoglu, Caroline Uhler, G.V. Shivashankar
Scientific Reports 7, Article 17946

Counting Markov equivalence classes by number of immoralities [arXiv, workshop link]
Adityanarayanan Radhakrishnan, Liam Solus, Caroline Uhler
UAI Special Workshop on Causality