| Anchored correlation explanation: Topic modeling with minimal domain knowledge RJ Gallagher, K Reing, D Kale, G Ver Steeg Transactions of the Association for Computational Linguistics 5, 529-542, 2017 | 193 | 2017 |
| Improving generalization by controlling label-noise information in neural network weights H Harutyunyan, K Reing, G Ver Steeg, A Galstyan International Conference on Machine Learning, 4071-4081, 2020 | 55 | 2020 |
| Toward interpretable topic discovery via anchored correlation explanation K Reing, DC Kale, GV Steeg, A Galstyan arXiv preprint arXiv:1606.07043, 2016 | 18 | 2016 |
| Discovering higher-order interactions through neural information decomposition K Reing, G Ver Steeg, A Galstyan Entropy 23 (1), 79, 2021 | 4 | 2021 |
| Sifting common information from many variables GV Steeg, S Gao, K Reing, A Galstyan arXiv preprint arXiv:1606.02307, 2016 | 4 | 2016 |
| Sifting Common Information from Many Variables. G Ver Steeg, S Gao, K Reing, A Galstyan IJCAI, 2885-2892, 2017 | 3 | 2017 |
| Influence decompositions for neural network attribution K Reing, G Ver Steeg, A Galstyan International Conference on Artificial Intelligence and Statistics, 2710-2718, 2021 | 2 | 2021 |
| Maximizing multivariate information with error-correcting codes K Reing, G Ver Steeg, A Galstyan IEEE Transactions on Information Theory 66 (5), 2683-2695, 2019 | 2 | 2019 |
| Sifting Common Information from Many Variables G Ver Steeg, S Gao, K Reing, A Galstyan stat 1050, 9, 2016 | | 2016 |
