Articles with public access mandates - Adityanarayanan RadhakrishnanLearn more
Available somewhere: 11
Multi-domain translation between single-cell imaging and sequencing data using autoencoders
KD Yang, A Belyaeva, S Venkatachalapathy, K Damodaran, A Katcoff, ...
Nature communications 12 (1), 31, 2021
Mandates: US National Science Foundation, US Department of Defense, US National …
Overparameterized neural networks implement associative memory
A Radhakrishnan, M Belkin, C Uhler
Proceedings of the National Academy of Sciences 117 (44), 27162-27170, 2020
Mandates: US National Science Foundation, US Department of Defense
Machine learning for nuclear mechano-morphometric biomarkers in cancer diagnosis
A Radhakrishnan, K Damodaran, AC Soylemezoglu, C Uhler, ...
Scientific reports 7 (1), 17946, 2017
Mandates: US National Science Foundation, US Department of Defense
Causal network models of SARS-CoV-2 expression and aging to identify candidates for drug repurposing
A Belyaeva, L Cammarata, A Radhakrishnan, C Squires, KD Yang, ...
Nature communications 12 (1), 1024, 2021
Mandates: US National Science Foundation, US Department of Defense, US National …
Cross-modal autoencoder framework learns holistic representations of cardiovascular state
A Radhakrishnan, SF Friedman, S Khurshid, K Ng, P Batra, SA Lubitz, ...
Nature Communications 14 (1), 2436, 2023
Mandates: US National Science Foundation, US Department of Defense, US National …
Simple, fast, and flexible framework for matrix completion with infinite width neural networks
A Radhakrishnan, G Stefanakis, M Belkin, C Uhler
Proceedings of the National Academy of Sciences 119 (16), e2115064119, 2022
Mandates: US National Science Foundation, US Department of Defense
Wide and deep neural networks achieve consistency for classification
A Radhakrishnan, M Belkin, C Uhler
Proceedings of the National Academy of Sciences 120 (14), e2208779120, 2023
Mandates: US National Science Foundation, US Department of Defense, US National …
Increasing depth leads to U-shaped test risk in over-parameterized convolutional networks
E Nichani, A Radhakrishnan, C Uhler
arXiv preprint arXiv:2010.09610, 2020
Mandates: US National Science Foundation, US Department of Defense
Counting Markov equivalence classes for DAG models on trees
A Radhakrishnan, L Solus, C Uhler
Discrete Applied Mathematics 244, 170-185, 2018
Mandates: US National Science Foundation, US Department of Defense
Transfer learning with kernel methods
A Radhakrishnan, M Ruiz Luyten, N Prasad, C Uhler
Nature Communications 14 (1), 5570, 2023
Mandates: US National Science Foundation, US Department of Defense, US National …
Synthetic Lethality Screening with Recursive Feature Machines
C Cai, A Radhakrishnan, C Uhler
bioRxiv, 2023
Mandates: US Department of Defense, US National Institutes of Health
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