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ORCIDAaron Schein
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2020 – today
- 2024
[c13]Kevin Du, Vésteinn Snæbjarnarson, Niklas Stoehr, Jennifer C. White, Aaron Schein, Ryan Cotterell:
Context versus Prior Knowledge in Language Models. ACL (1) 2024: 13211-13235- [c12]Niklas Stoehr, Kevin Du, Vésteinn Snæbjarnarson, Robert West, Ryan Cotterell, Aaron Schein:
Activation Scaling for Steering and Interpreting Language Models. EMNLP (Findings) 2024: 8189-8200 - [i14]Kevin Du, Vésteinn Snæbjarnarson, Niklas Stoehr, Jennifer C. White, Aaron Schein, Ryan Cotterell:
Context versus Prior Knowledge in Language Models. CoRR abs/2404.04633 (2024) - [i13]Evan Dong, Aaron Schein, Yixin Wang, Nikhil Garg:
Addressing Discretization-Induced Bias in Demographic Prediction. CoRR abs/2405.16762 (2024) - [i12]Niklas Stoehr, Kevin Du, Vésteinn Snæbjarnarson, Robert West, Ryan Cotterell, Aaron Schein:
Activation Scaling for Steering and Interpreting Language Models. CoRR abs/2410.04962 (2024) - [i11]Anjali Nagulpally, Patrick Flaherty, Aaron Schein:
Doubly Non-Central Beta Matrix Factorization for Stable Dimensionality Reduction of Bounded Support Matrix Data. CoRR abs/2410.18425 (2024) - 2023
- [c11]Niklas Stoehr, Lucas Torroba Hennigen, Josef Valvoda, Robert West, Ryan Cotterell, Aaron Schein:
An Ordinal Latent Variable Model of Conflict Intensity. ACL (1) 2023: 4817-4830 - [c10]Niklas Stoehr, Benjamin J. Radford
, Ryan Cotterell, Aaron Schein:
The Ordered Matrix Dirichlet for State-Space Models. AISTATS 2023: 1888-1903 - [c9]Niklas Stoehr, Ryan Cotterell, Aaron Schein:
Sentiment as an Ordinal Latent Variable. EACL 2023: 103-115 - [i10]Sean O'Hagan, Aaron Schein:
Measurement in the Age of LLMs: An Application to Ideological Scaling. CoRR abs/2312.09203 (2023) - 2022
- [e3]Javier Antorán, Arno Blaas, Fan Feng, Sahra Ghalebikesabi, Ian Mason, Melanie F. Pradier, David Rohde, Francisco J. R. Ruiz, Aaron Schein:
Proceedings on "I Can't Believe It's Not Better! - Understanding Deep Learning Through Empirical Falsification" at NeurIPS 2022 Workshops, 03 December 2022, New Orleans, Louisiana, USA. Proceedings of Machine Learning Research 187, PMLR 2022 [contents] - [i9]Niklas Stoehr, Lucas Torroba Hennigen, Josef Valvoda, Robert West, Ryan Cotterell, Aaron Schein:
An Ordinal Latent Variable Model of Conflict Intensity. CoRR abs/2210.03971 (2022) - [i8]Niklas Stoehr, Benjamin J. Radford, Ryan Cotterell, Aaron Schein:
The Ordered Matrix Dirichlet for Modeling Ordinal Dynamics. CoRR abs/2212.04130 (2022) - 2021
- [c8]Aaron Schein, Anjali Nagulpally, Hanna M. Wallach, Patrick Flaherty:
Doubly non-central beta matrix factorization for DNA methylation data. UAI 2021: 1895-1904 - [c7]Aaron Schein, Keyon Vafa, Dhanya Sridhar, Victor Veitch, Jeffrey Quinn, James Moffet, David M. Blei, Donald P. Green:
Assessing the Effects of Friend-to-Friend Texting onTurnout in the 2018 US Midterm Elections. WWW 2021: 2025-2036 - [e2]Melanie F. Pradier, Aaron Schein, Stephanie L. Hyland, Francisco J. R. Ruiz, Jessica Zosa Forde:
I (Still) Can't Believe It's Not Better! Workshop at NeurIPS 2021, Virtual Workshop, December 13, 2021. Proceedings of Machine Learning Research 163, PMLR 2021 [contents] - [i7]Aaron Schein, Anjali Nagulpally, Hanna M. Wallach, Patrick Flaherty:
Doubly Non-Central Beta Matrix Factorization for DNA Methylation Data. CoRR abs/2106.06691 (2021) - 2020
- [e1]Jessica Zosa Forde, Francisco J. R. Ruiz, Melanie F. Pradier, Aaron Schein:
"I Can't Believe It's Not Better!" at NeurIPS Workshops, Virtual, December 12, 2020. Proceedings of Machine Learning Research 137, PMLR 2020 [contents]
2010 – 2019
- 2019
- [c6]Aaron Schein, Zhiwei Steven Wu, Alexandra Schofield, Mingyuan Zhou, Hanna M. Wallach:
Locally Private Bayesian Inference for Count Models. ICML 2019: 5638-5648 - [c5]Aaron Schein, Scott W. Linderman, Mingyuan Zhou, David M. Blei, Hanna M. Wallach:
Poisson-Randomized Gamma Dynamical Systems. NeurIPS 2019: 781-792 - [i6]Aaron Schein, Scott W. Linderman, Mingyuan Zhou, David M. Blei, Hanna M. Wallach:
Poisson-Randomized Gamma Dynamical Systems. CoRR abs/1910.12991 (2019) - 2018
- [i5]Aaron Schein, Zhiwei Steven Wu, Mingyuan Zhou, Hanna M. Wallach:
Locally Private Bayesian Inference for Count Models. CoRR abs/1803.08471 (2018) - 2017
- [i4]Aaron Schein, Mingyuan Zhou, Hanna M. Wallach:
Poisson-Gamma Dynamical Systems. CoRR abs/1701.05573 (2017) - 2016
- [c4]Aaron Schein, Mingyuan Zhou, David M. Blei, Hanna M. Wallach:
Bayesian Poisson Tucker Decomposition for Learning the Structure of International Relations. ICML 2016: 2810-2819 - [c3]Aaron Schein, Hanna M. Wallach, Mingyuan Zhou:
Poisson-Gamma dynamical systems. NIPS 2016: 5006-5014 - [i3]Aaron Schein, Mingyuan Zhou, David M. Blei, Hanna M. Wallach:
Bayesian Poisson Tucker Decomposition for Learning the Structure of International Relations. CoRR abs/1606.01855 (2016) - 2015
- [c2]Aaron Schein, John W. Paisley, David M. Blei, Hanna M. Wallach:
Bayesian Poisson Tensor Factorization for Inferring Multilateral Relations from Sparse Dyadic Event Counts. KDD 2015: 1045-1054 - [i2]Aaron Schein, John W. Paisley, David M. Blei, Hanna M. Wallach:
Bayesian Poisson Tensor Factorization for Inferring Multilateral Relations from Sparse Dyadic Event Counts. CoRR abs/1506.03493 (2015) - 2013
- [i1]Aaron Schein, Juston Moore, Hanna M. Wallach:
Inferring Multilateral Relations from Dynamic Pairwise Interactions. CoRR abs/1311.3982 (2013) - 2012
- [c1]Keith J. Miller, Elizabeth Schroeder Richerson, Sarah McLeod, James Finley, Aaron Schein:
International Multicultural Name Matching Competition: Design, Execution, Results, and Lessons Learned. LREC 2012: 3111-3117
Coauthor Index
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