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Kelly Buchanan
Kelly Buchanan
Verified email at columbia.edu - Homepage
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Cited by
Cited by
Year
Voltage imaging and optogenetics reveal behaviour-dependent changes in hippocampal dynamics
Y Adam, JJ Kim, S Lou, Y Zhao, ME Xie, D Brinks, H Wu, ...
Nature 569 (7756), 413-417, 2019
3262019
Plex: Towards reliability using pretrained large model extensions
D Tran, J Liu, MW Dusenberry, D Phan, M Collier, J Ren, K Han, Z Wang, ...
arXiv preprint arXiv:2207.07411, 2022
1062022
Deep Graph Pose: a semi-supervised deep graphical model for improved animal pose tracking
A Wu, EK Buchanan, M Whiteway, M Schartner, G Meijer, JP Noel, ...
Advances in Neural Information Processing Systems 33, 6040--6052, 2020
53*2020
Penalized matrix decomposition for denoising, compression, and improved demixing of functional imaging data
EK Buchanan, I Kinsella, D Zhou, R Zhu, P Zhou, F Gerhard, J Ferrante, ...
BioRxiv, 334706, 2018
47*2018
Deep ensembles work, but are they necessary?
T Abe, EK Buchanan, G Pleiss, R Zemel, JP Cunningham
Advances in Neural Information Processing Systems 35, 33646-33660, 2022
432022
Neuroscience Cloud Analysis As a Service: An open-source platform for scalable, reproducible data analysis
T Abe, I Kinsella, S Saxena, EK Buchanan, J Couto, J Briggs, SL Kitt, ...
Neuron 110 (17), 2771-2789. e7, 2022
312022
Partitioning variability in animal behavioral videos using semi-supervised variational autoencoders
MR Whiteway, D Biderman, Y Friedman, M Dipoppa, EK Buchanan, A Wu, ...
PLoS computational biology 17 (9), e1009439, 2021
27*2021
Reproducibility of in-vivo electrophysiological measurements in mice
International Brain Laboratory, K Banga, J Benson, N Bonacchi, ...
bioRxiv, 2022.05. 09.491042, 2022
132022
Pathologies of predictive diversity in deep ensembles
T Abe, EK Buchanan, G Pleiss, JP Cunningham
arXiv preprint arXiv:2302.00704, 2023
82023
Quantifying the behavioral dynamics of C. elegans with autoregressive hidden Markov models
EK Buchanan, A Lipschitz, SW Linderman, L Paninski
Workshop on Worm’s Neural Information Processing at the 31st Conference on …, 2017
82017
The Best Deep Ensembles Sacrifice Predictive Diversity
T Abe, EK Buchanan, G Pleiss, JP Cunningham
I Can't Believe It's Not Better Workshop: Understanding Deep Learning …, 2022
62022
Semi-supervised sequence modeling for improved behavioral segmentation
MR Whiteway, ES Schaffer, A Wu, EK Buchanan, OF Onder, N Mishra, ...
bioRxiv, 2021.06. 16.448685, 2021
42021
Video hardware and software for the International Brain Laboratory
D Birman, N Bonacchi, K Buchanan, G Chapuis, JM Huntenburg, G Meijer, ...
32022
Neuroscience cloud analysis as a service
T Abe, I Kinsella, S Saxena, EK Buchanan, J Couto, J Briggs, SL Kitt, ...
bioRxiv, 2020
3*2020
Constrained matrix factorization methods for denoising and demixing voltage imaging data
EK Buchanan, J Friedrich, I Kinsella, P Stinson, P Zhou, F Gerhard, ...
COSYNE, 2018
32018
Reliability benchmarks for semantic segmentation
EK Buchanan, MW Dusenberry, J Ren, KP Murphy, B Lakshminarayanan, ...
NeurIPS 2022 Workshop on Distribution Shifts: Connecting Methods and …, 2022
1*2022
The Effects of Ensembling on Long-Tailed Data
EK Buchanan, G Pleiss, Y Wang, JP Cunningham
NeurIPS 2023 Workshop Heavy Tails in Machine Learning, 2023
2023
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