| Method, apparatus, and system for in-vehicle data selection for feature detection model creation and maintenance N Dronen, S O'hara, V Shestak US Patent 11,263,549, 2022 | 22 | 2022 |
| Effective sampling for large-scale automated writing evaluation systems N Dronen, PW Foltz, K Habermehl Proceedings of the second (2015) ACM conference on learning@ scale, 3-10, 2015 | 20 | 2015 |
| Machine learning a feature detector using synthetic training data B Keserich, S O'hara, N Dronen US Patent 10,839,262, 2020 | 12 | 2020 |
| Resource allocation in distributed processing systems NA Dronen, PW Foltz, H Garner, MT Loring, V Kapoor US Patent 10,148,589, 2018 | 12 | 2018 |
| Method, apparatus, and system for dynamic adaptation of an in-vehicle feature detector V Shestak, S O'hara, N Dronen US Patent 10,733,484, 2020 | 9 | 2020 |
| Resource allocation in distributed processing systems NA Dronen, PW Foltz, H Garner, MT Loring, V Kapoor US Patent 10,153,984, 2018 | 8 | 2018 |
| Adaptive block floating-point for analog deep learning hardware A Basumallik, D Bunandar, N Dronen, N Harris, L Levkova, C McCarter, ... arXiv preprint arXiv:2205.06287, 2022 | 7 | 2022 |
| Resource allocation in distributed processing systems NA Dronen, PW Foltz, H Garner, MT Loring, V Kapoor US Patent 10,938,738, 2021 | 6 | 2021 |
| Resource allocation in distributed processing systems NA Dronen, PW Foltz, H Garner, MT Loring, V Kapoor US Patent 10,560,397, 2020 | 6 | 2020 |
| Automated feedback in a large-scale implementation of a formative writing system: Implications for improving student writing PW Foltz, M Rosenstein, N Dronen, S Dooley annual meeting of the American Educational Research Association …, 2014 | 6 | 2014 |
| Look-ups are not (yet) all you need for deep learning inference C McCarter, N Dronen arXiv preprint arXiv:2207.05808, 2022 | 5 | 2022 |
| Machine learning model training using an analog processor D Bunandar, L Levkova, N Dronen, L Nair, D Widemann, D Walter, ... US Patent App. 17/537,156, 2022 | 3 | 2022 |
| Correcting writing errors with convolutional neural networks NA Dronen University of Colorado at Boulder, 2016 | 3 | 2016 |
| Techniques for adapting neural networks to devices N Dronen, T Lazovich, A Basumallik, D Bunandar US Patent App. 17/390,764, 2022 | 2 | 2022 |
| Parking lot instance segmentation from satellite imagery through associative embeddings T Berry, N Dronen, B Jackson, I Endres Proceedings of the 27th ACM SIGSPATIAL International Conference on Advances …, 2019 | 2 | 2019 |
| Return probability and k-step measures N Dronen, Q Lv arXiv preprint arXiv:1105.4479, 2011 | 2 | 2011 |
| How lexical is bilingual lexicon induction? H Kohli, H Feng, N Dronen, C McCarter, S Moeini, A Kebarighotbi arXiv preprint arXiv:2404.04221, 2024 | 1 | 2024 |
| Methods, apparatuses, and computer program products using a repeated convolution-based attention module for improved neural network implementations AS Gill, N Dronen, S Roy, R Balu US Patent 11,651,191, 2023 | 1 | 2023 |
| The accuracy of low-bitwidth neural networks by regularizing the higher-order moments of weights and hidden states N Dronen, TJ Kenney, T Lazovich, A Basumallik, D Bunandar US Patent App. 17/672,627, 2022 | 1 | 2022 |
| Eidetic Learning: an Efficient and Provable Solution to Catastrophic Forgetting N Dronen, R Balestriero arXiv preprint arXiv:2502.09500, 2025 | | 2025 |
Peter W FoltzResearch Professor, Institute of Cognitive Science Univ of ColoradoE-mailová adresa ověřena na: colorado.edu