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ORCIDMartin T. Wells
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- affiliation: Cornell University, Ithaca, NY, USA
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2020 – today
- 2025
[i13]Daniel Andrew Coulson, Martin T. Wells:
Boltzmann convolutions and Welford mean-variance layers with an application to time series forecasting and classification. CoRR abs/2503.04956 (2025)- [i12]Giuseppe Di Caro, Vahagn Kirakosyan, Alexander G. Abanov, Luca Candelori, Nadine Hartmann, Ernest T. Lam, Kharen Musaelian, Ryan Samson, Dario Villani, Martin T. Wells, Richard J. Wenstrup, Mengjia Xu:
Quantum Cognition Machine Learning for Forecasting Chromosomal Instability. CoRR abs/2506.03199 (2025) - [i11]Suvadip Sana, Daniel Brous, Martin T. Wells, Moon Duchin:
Quantitative Relaxations of Arrow's Axioms. CoRR abs/2506.12961 (2025) - 2024
- [i10]Tejas Ramdas, Martin T. Wells:
Bellwether Trades: Characteristics of Trades influential in Predicting Future Price Movements in Markets. CoRR abs/2409.05192 (2024) - [i9]Luca Candelori, Alexander G. Abanov, Jeffrey Berger, Cameron J. Hogan, Vahagn Kirakosyan, Kharen Musaelian, Ryan Samson, James E. T. Smith, Dario Villani, Martin T. Wells, Mengjia Xu:
Robust estimation of the intrinsic dimension of data sets with quantum cognition machine learning. CoRR abs/2409.12805 (2024) - [i8]Sarah Tan, Keri Mallari, Julius Adebayo, Albert Gordo, Martin T. Wells, Kori Inkpen:
How Aligned are Generative Models to Humans in High-Stakes Decision-Making? CoRR abs/2410.15471 (2024) - 2023
- [j7]Haim Bar, Martin T. Wells:
On graphical models and convex geometry. Comput. Stat. Data Anal. 187: 107800 (2023) - 2022
- [i7]Haoxuan Wu, David S. Matteson
, Martin T. Wells:
Interpretable Latent Variables in Deep State Space Models. CoRR abs/2203.02057 (2022) - 2021
- [c3]Skyler Seto, Martin T. Wells, Wenyu Zhang:
HALO: Learning to Prune Neural Networks with Shrinkage. SDM 2021: 558-566 - [i6]Liao Zhu, Haoxuan Wu, Martin T. Wells:
A News-based Machine Learning Model for Adaptive Asset Pricing. CoRR abs/2106.07103 (2021) - [i5]Liao Zhu, Ningning Sun, Martin T. Wells:
Clustering Structure of Microstructure Measures. CoRR abs/2107.02283 (2021) - 2020
- [c2]Sarah Tan, Matvey Soloviev, Giles Hooker, Martin T. Wells:
Tree Space Prototypes: Another Look at Making Tree Ensembles Interpretable. FODS 2020: 23-34 - [i4]Daqian Sun, Martin T. Wells:
Robust Matrix Completion with Mixed Data Types. CoRR abs/2005.12415 (2020) - [i3]Skyler Seto, Martin T. Wells, Wenyu Zhang:
Hierarchical Adaptive Lasso: Learning Sparse Neural Networks with Shrinkage via Single Stage Training. CoRR abs/2008.10183 (2020)
2010 – 2019
- 2019
- [i2]Benjamin R. Baer, Daniel E. Gilbert, Martin T. Wells:
Fairness criteria through the lens of directed acyclic graphical models. CoRR abs/1906.11333 (2019) - 2018
- [j6]Didier Chételat, Rajendran Narayanan, Martin T. Wells:
On the domain of attraction of a Tracy-Widom law with applications to testing multiple largest roots. J. Multivar. Anal. 165: 132-142 (2018) - 2016
- [j5]Dominique Fourdrinier, Fatiha Mezoued, Martin T. Wells:
Estimation of the inverse scatter matrix of an elliptically symmetric distribution. J. Multivar. Anal. 143: 32-55 (2016) - [j4]Didier Chételat, Martin T. Wells:
Improved second order estimation in the singular multivariate normal model. J. Multivar. Anal. 147: 1-19 (2016) - [i1]Hui Fen Tan, Giles Hooker, Martin T. Wells:
Tree Space Prototypes: Another Look at Making Tree Ensembles Interpretable. CoRR abs/1611.07115 (2016)
2000 – 2009
- 2009
- [j3]William Anderson, Martin T. Wells:
The Exact Distribution of the Condition Number of a Gaussian Matrix. SIAM J. Matrix Anal. Appl. 31(3): 1125-1130 (2009) - 2008
- [j2]Min Zhang, Dabao Zhang, Martin T. Wells:
Variable selection for large p small n regression models with incomplete data: Mapping QTL with epistases. BMC Bioinform. 9 (2008) - 2005
- [j1]Dabao Zhang, Martin T. Wells, Christine D. Smart, William E. Fry:
Bayesian Normalization and Identification for Differential Gene Expression Data. J. Comput. Biol. 12(4): 391-406 (2005)
1990 – 1999
- 1993
- [c1]Yu Lo Cyrus Chang, Leslie C. Lander, Horng-Shing Lu, Martin T. Wells:
Bayesian Analysis for Fault Location in Homogeneous Distributed Systems. SRDS 1993: 44-53
Coauthor Index
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