Discrete flows: Invertible generative models of discrete data D Tran, K Vafa, K Agrawal, L Dinh, B Poole Advances in Neural Information Processing Systems 32, 2019 | 116 | 2019 |
Text-based ideal points K Vafa, S Naidu, DM Blei arXiv preprint arXiv:2005.04232, 2020 | 44 | 2020 |
Rationales for sequential predictions K Vafa, Y Deng, DM Blei, AM Rush arXiv preprint arXiv:2109.06387, 2021 | 25 | 2021 |
Training deep Gaussian processes with sampling K Vafa NIPS 2016 Workshop on Advances in Approximate Bayesian Inference, 2016 | 9 | 2016 |
A digital field experiment reveals large effects of friend-to-friend texting on voter turnout A Schein, K Vafa, D Sridhar, V Veitch, J Quinn, J Moffet, DM Blei, ... Available at SSRN 3696179, 2020 | 7 | 2020 |
Training and inference for deep Gaussian processes K Vafa | 7 | 2016 |
Price discrimination in the princeton review’s online sat tutoring service K Vafa, C Haigh, A Leung, N Yonack Technology Science 2015090101, 2015 | 7 | 2015 |
Assessing the Effects of Friend-to-Friend Texting onTurnout in the 2018 US Midterm Elections A Schein, K Vafa, D Sridhar, V Veitch, J Quinn, J Moffet, DM Blei, ... Proceedings of the Web Conference 2021, 2025-2036, 2021 | 3 | 2021 |
CAREER: Transfer Learning for Economic Prediction of Labor Sequence Data K Vafa, E Palikot, T Du, A Kanodia, S Athey, DM Blei arXiv preprint arXiv:2202.08370, 2022 | 2 | 2022 |
Revisiting Topic-Guided Language Models C Zheng, K Vafa, DM Blei arXiv preprint arXiv:2312.02331, 2023 | 1 | 2023 |
Decomposing Changes in the Gender Wage Gap over Worker Careers K Vafa, S Athey, DM Blei NBER Summer Institute, Boston, MA, 2023 | 1 | 2023 |
An invariant learning characterization of controlled text generation C Zheng, C Shi, K Vafa, A Feder, DM Blei arXiv preprint arXiv:2306.00198, 2023 | 1 | 2023 |
An Invariant Learning Characterization of Controlled Text Generation C Shi, C Zheng, K Vafa, A Feder, D Blei NeurIPS 2022 Workshop on Distribution Shifts: Connecting Methods and …, 2022 | 1 | 2022 |
CAREER: Economic prediction of labor sequence data under distribution shift K Vafa, E Palikot, T Du, A Kanodia, S Athey, D Blei NeurIPS 2022 Workshop on Distribution Shifts: Connecting Methods and …, 2022 | 1 | 2022 |
Learning Transferrable Representations of Career Trajectories for Economic Prediction K Vafa, E Palikot, T Du, A Kanodia, S Athey, DM Blei CoRR, 2022 | 1 | 2022 |
Lookahead Bias in Pretrained Language Models SK Sarkar, K Vafa Available at SSRN, 2024 | | 2024 |
CAREER: A Foundation Model for Labor Sequence Data K Vafa, E Palikot, T Du, A Kanodia, S Athey, D Blei Transactions on Machine Learning Research, 2023 | | 2023 |
Interpretable Machine Learning for the Social Sciences: Applications in Political Science and Labor Economics K Vafa Columbia University, 2023 | | 2023 |
CAREER: Transfer Learning for Economic Prediction of Labor Data K Vafa, E Palikot, T Du, A Kanodia, S Athey, D Blei | | 2022 |