Nicolo Colombo
Title
Cited by
Cited by
Year
Higher spin gravity amplitudes from zero-form charges
N Colombo, P Sundell
arXiv preprint arXiv:1208.3880, 2012
662012
A minimal BV action for Vasiliev’s four-dimensional higher spin gravity
N Boulanger, N Colombo, P Sundell
Journal of High Energy Physics 2012 (10), 1-36, 2012
422012
Bayesian semi-supervised learning with graph gaussian processes
YC Ng, N Colombo, R Silva
arXiv preprint arXiv:1809.04379, 2018
352018
Twistor space observables and quasi-amplitudes in 4D higher-spin gravity
N Colombo, P Sundell
Journal of High Energy Physics 2011 (11), 1-47, 2011
352011
Tensor decomposition via joint matrix Schur decomposition
N Colombo, N Vlassis
International Conference on Machine Learning, 2820-2828, 2016
182016
FastMotif: spectral sequence motif discovery
N Colombo, N Vlassis
Bioinformatics 31 (16), 2623-2631, 2015
162015
Expression of the Parkinson’s disease-associated gene alpha-synuclein is regulated by the neuronal cell fate determinant TRIM32
MAS Pavlou, N Colombo, S Fuertes-Alvarez, S Nicklas, LG Cano, ...
Molecular neurobiology 54 (6), 4257-4270, 2017
152017
Approximate joint matrix triangularization
N Colombo, N Vlassis
arXiv preprint arXiv:1607.00514, 2016
52016
Training conformal predictors
N Colombo, V Vovk
https://arxiv.org/abs/2005.07037, 2020
42020
A posteriori error bounds for joint matrix decomposition problems
N Colombo, N Vlassis
Advances in Neural Information Processing Systems 29, 4943-4950, 2016
42016
Experimental design trade-offs for gene regulatory network inference: An in silico study of the yeast Saccharomyces cerevisiae cell cycle
J Markdahl, N Colombo, J Thunberg, J Gonçalves
2017 IEEE 56th Annual Conference on Decision and Control (CDC), 423-428, 2017
32017
Adapting by Pruning: A Case Study on BERT
Y Gao, N Colombo, W Wang
arXiv preprint arXiv:2105.03343, 2021
12021
Disentangling neural architectures and weights: A case study in supervised classification
N Colombo, Y Gao
arXiv preprint arXiv:2009.05346, 2020
12020
Tomography of the London underground: a scalable model for origin-destination data
N Colombo, R Silva, SM Kang
Advances in Neural Information Processing Systems 30, 2017
12017
Stable Spectral Learning Based on Schur Decomposition.
N Colombo, N Vlassis
UAI, 220-227, 2015
12015
Differentiable Architecture Pruning for Transfer Learning
N Colombo, Y Gao
arXiv preprint arXiv:2107.03375, 2021
2021
Multiple Metric Learning for Structured Data
N Colombo
https://arxiv.org/abs/2002.05747, 2020
2020
Counterfactual Distribution Regression for Structured Inference
N Colombo, R Silva, SM Kang, A Gretton
arXiv preprint arXiv:1908.07193, 2019
2019
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Articles 1–18