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Cole Hurwitz
Cole Hurwitz
Postdoctoral Research Scientist, Zuckerman Institute, Columbia University
Verified email at columbia.edu - Homepage
Title
Cited by
Cited by
Year
SpikeInterface, a unified framework for spike sorting
AP Buccino*, CL Hurwitz*, S Garcia, J Magland, JH Siegle, R Hurwitz, ...
Elife 9, e61834, 2020
1792020
SpikeForest, reproducible web-facing ground-truth validation of automated neural spike sorters
J Magland, JJ Jun, E Lovero, AJ Morley, CL Hurwitz, AP Buccino, ...
Elife 9, e55167, 2020
782020
Building population models for large-scale neural recordings: opportunities and pitfalls
C Hurwitz*, N Kudryashova*, A Onken, MH Hennig
Current Opinion in Neurobiology 70, Pages 64-73, 2021
322021
Targeted neural dynamical modeling
C Hurwitz, A Srivastava, K Xu, J Jude, M Perich, L Miller, M Hennig
Advances in Neural Information Processing Systems 34, 29379-29392, 2021
242021
Scaling spike detection and sorting for next-generation electrophysiology
MH Hennig, C Hurwitz, M Sorbaro
In Vitro Neuronal Networks: From Culturing Methods to Neuro-Technological …, 2019
232019
Scalable Spike Source Localization in Extracellular Recordings using Amortized Variational Inference
C Hurwitz, K Xu, A Srivastava, A Buccino, M Hennig
Advances in Neural Information Processing Systems 32, 4726–4738, 2019
182019
Reproducibility of in-vivo electrophysiological measurements in mice
International Brain Laboratory, K Banga, J Benson, N Bonacchi, ...
bioRxiv, 2022.05. 09.491042, 2022
132022
Lightning Pose: improved animal pose estimation via semi-supervised learning, Bayesian ensembling and cloud-native open-source tools
D Biderman, MR Whiteway, C Hurwitz, N Greenspan, RS Lee, ...
Nature Methods, 1-13, 2024
102024
Ultra-high density electrodes improve detection, yield, and cell type identification in neuronal recordings
Z Ye, AM Shelton, JR Shaker, J Boussard, J Colonell, D Birman, S Manavi, ...
bioRxiv, 2023
82023
not-so-BigGAN: Generating High-Fidelity Images on Small Compute with Wavelet-based Super-Resolution
S Han*, A Srivastava*, C Hurwitz*, P Sattigeri, DD Cox
arXiv preprint arXiv:2009.04433, 2020
8*2020
Spike sorting pipeline for the International Brain Laboratory
K Banga, J Boussard, GA Chapuis, M Faulkner, KD Harris, ...
72022
DARTsort: A modular drift tracking spike sorter for high-density multi-electrode probes
J Boussard*, C Windolf*, C Hurwitz*, HD Lee, H Yu, O Winter, L Paninski
bioRxiv, 2023.08. 11.553023, 2023
42023
Improving the Reconstruction of Disentangled Representation Learners via Multi-Stage Modelling
A Srivastava*, Y Bansal*, Y Ding*, C Hurwitz*, K Xu, B Egger, P Sattigeri, ...
arXiv preprint arXiv:2010.13187, 2020
42020
Spike sorting pipeline for the International Brain Laboratory
G Chapuis, M Faulkner, KD Harris, JM Huntenburg, C Hurwitz, HD Lee, ...
channels 10 (6), 2022
32022
Bypassing spike sorting: Density-based decoding using spike localization from dense multielectrode probes
Y Zhang, T He, J Boussard, C Windolf, O Winter, E Trautmann, N Roth, ...
Advances in Neural Information Processing Systems 36, 2024
22024
Towards a "universal translator" for neural dynamics at single-cell, single-spike resolution
Y Zhang, Y Wang, D Jimenez-Beneto, Z Wang, M Azabou, B Richards, ...
arXiv preprint arXiv:2407.14668, 2024
2024
Towards robust and generalizable representations of extracellular data using contrastive learning
A Vishnubhotla, C Loh, A Srivastava, L Paninski, C Hurwitz
Advances in Neural Information Processing Systems 36, 2024
2024
Scalable software and models for large-scale extracellular recordings
CL Hurwitz
The University of Edinburgh, 2022
2022
Supplementary Materials: Towards robust and generalizable representations of extracellular data using contrastive learning
A Vishnubhotla, C Loh, L Paninski, A Srivastava, C Hurwitz
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Articles 1–19