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Adityanarayanan Radhakrishnan
Adityanarayanan Radhakrishnan
Other namesAdit Radhakrishnan, Adit Radha
Verified email at seas.harvard.edu - Homepage
Title
Cited by
Cited by
Year
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
1202021
Overparameterized neural networks implement associative memory
A Radhakrishnan, M Belkin, C Uhler
Proceedings of the National Academy of Sciences 117 (44), 27162-27170, 2020
112*2020
Machine learning for nuclear mechano-morphometric biomarkers in cancer diagnosis
A Radhakrishnan, K Damodaran, AC Soylemezoglu, C Uhler, ...
Scientific reports 7 (1), 17946, 2017
552017
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
522021
Mechanism for feature learning in neural networks and backpropagation-free machine learning models
A Radhakrishnan, D Beaglehole, P Pandit, M Belkin
Science, 2024
39*2024
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
232022
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
19*2020
Counting Markov equivalence classes for DAG models on trees
A Radhakrishnan, L Solus, C Uhler
Discrete Applied Mathematics 244, 170-185, 2018
192018
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
172023
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
152023
Counting Markov equivalence classes by number of immoralities
A Radhakrishnan, L Solus, C Uhler
arXiv preprint arXiv:1611.07493, 2016
152016
Quadratic models for understanding neural network dynamics
L Zhu, C Liu, A Radhakrishnan, M Belkin
arXiv preprint arXiv:2205.11787, 2022
142022
Patchnet: interpretable neural networks for image classification
A Radhakrishnan, C Durham, A Soylemezoglu, C Uhler
arXiv preprint arXiv:1705.08078, 2017
122017
A mechanism for producing aligned latent spaces with autoencoders
S Jain, A Radhakrishnan, C Uhler
arXiv preprint arXiv:2106.15456, 2021
92021
Multi-domain translation between single-cell imaging and sequencing data using autoencoders. Nat. Commun. 12, 31
KD Yang, A Belyaeva, S Venkatachalapathy, K Damodaran, ...
82021
Linear convergence of generalized mirror descent with time-dependent mirrors
A Radhakrishnan, M Belkin, C Uhler
arXiv preprint arXiv:2009.08574, 2020
7*2020
Mechanism of feature learning in convolutional neural networks
D Beaglehole, A Radhakrishnan, P Pandit, M Belkin
arXiv preprint arXiv:2309.00570, 2023
62023
Catapults in sgd: spikes in the training loss and their impact on generalization through feature learning
L Zhu, C Liu, A Radhakrishnan, M Belkin
arXiv preprint arXiv:2306.04815, 2023
62023
On Alignment in Deep Linear Neural Networks
A Radhakrishnan, E Nichani, D Bernstein, C Uhler
arXiv preprint arXiv:2003.06340, 2020
6*2020
Transfer learning with kernel methods
A Radhakrishnan, M Ruiz Luyten, N Prasad, C Uhler
Nature Communications 14 (1), 5570, 2023
42023
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