Gonzalo Mena
Gonzalo Mena
University of Oxford
Verified email at columbia.edu - Homepage
Title
Cited by
Cited by
Year
Learning Latent Permutations With Gumbel-Sinkhorn Networks
G Mena, D Belanger, S Linderman, J Snoek
The Sixth International Conference on Learning Representations (ICLR), 2018
1112018
Statistical Bounds for Entropic Optimal Transport: Sample Complexity and the Central Limit Theorem
G Mena, J Weed
Advances in Neural Information Processing Systems 32, 2019
552019
NeuroPAL: a multicolor atlas for Whole-Brain neuronal identification in C. elegans
E Yemini, A Lin, A Nejatbakhsh, E Varol, R Sun, GE Mena, ADT Samuel, ...
Cell 184 (1), 272-288. e11, 2021
54*2021
Socioeconomic status determines COVID-19 incidence and related mortality in Santiago, Chile
GE Mena, PP Martinez, AS Mahmud, PA Marquet, CO Buckee, ...
Science 372 (6545), 2021
462021
Reparameterizing The Birkhoff Polytope for Variational Permutation Inference
SW Linderman, GE Mena, H Cooper, L Paninski, JP Cunningham
The 21nd International Conference on Artificial Intelligence and Statistics …, 2017
412017
Electrical Stimulus Artifact Cancellation and Neural Spike Detection on Large Multi-Electrode Arrays
GE Mena, LE Grosberg, S Madugula, P Hottowy, A Litke, J Cunningham, ...
PLoS computational biology 13 (11), e1005842, 2017
292017
Optimization of electrical stimulation for a high-fidelity artificial retina
NP Shah, S Madugula, L Grosberg, G Mena, P Tandon, P Hottowy, A Sher, ...
2019 9th International IEEE/EMBS Conference on Neural Engineering (NER), 714-718, 2019
142019
Sinkhorn Networks: Using Optimal Transport Techniques to Learn Permutations
G Mena, D Belanger, G Muņoz, J Snoek
NIPS workshop on Optimal Transport & Machine Learning, 2017
82017
On Quadrature Methods for Refractory Point Process Likelihoods
G Mena, L Paninski
Neural computation 26 (12), 2790-2797, 2014
82014
Statistical Atlas of C. elegans Neurons
E Varol, A Nejatbakhsh, R Sun, G Mena, E Yemini, O Hobert, L Paninski
International Conference on Medical Image Computing and Computer-Assisted …, 2020
72020
Large-scale Multi Electrode Array Spike Sorting Algorithm Introducing Concurrent Recording and Stimulation
G Mena, L Grosberg, F Kellison-Linn, E Chichilnisky, L Paninski
NIPS workshop on Statistical Methods for Understanding Neural Systems, 2015
42015
Sinkhorn EM: An Expectation-Maximization algorithm based on entropic optimal transport
G Mena, A Nejatbakhsh, E Varol, J Niles-Weed
arXiv preprint arXiv:2006.16548, 2020
32020
Toward Bayesian Permutation Inference for Identifying Neurons in C. elegans.
G Mena, S Linderman, D Belanger, J Snoek, J Cunningham, L Paninski
NIPS workshop on Worm's Neural Information Processing (WNIP)., 2017
22017
Sinkhorn Permutation Variational Marginal Inference
G Mena, E Varol, A Nejatbakhsh, E Yemini, L Paninski
2nd Symposium on Advances in Approximate Bayesian Inference, 2019
12019
A unified framework for de-duplication and population size estimation (contributed discussion)
N Ju, N Biswas, PE Jacob, G Mena, J O'Leary, E Pompe
Bayesian Analysis 15 (2), 2020
2020
Semi-automated cell identification in NeuroPAL C. elegans strains
G Mena, A Nejatbakhsh, R Sun, E Varol, E Yemini, L Paninski
2019
Statistical Machine Learning Methods for the Large-Scale Analysis of Neural Data
GE Mena
Columbia University, 2018
2018
Optimal Transport: Sample Complexity and the Central Limit Theorem
G Mena, J Niles-Weed
Reparameterizing the Birkhoff Polytope for Variational Permutation Inference: Supplementary Material
SW Linderman, GE Mena, H Cooper, L Paninski, JP Cunningham
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Articles 1–19