| Learning Sum-Product Networks with Direct and Indirect Variable Interactions A Rooshenas, D Lowd ICML'14, 2014 | 183 | 2014 |
| Learning Sum-Product Networks with Direct and Indirect Variable Interactions A Rooshenas, D Lowd Thirty-First International Conference on Machine Learning (ICML 14), 2014 | 183 | 2014 |
| Reducing Data Transmission in Wireless Sensor Networks Using Principal Component Analysis A Rooshenas, HR Rabiee, A Movaghar, MY Naderi Intelligent Sensors, Sensor Networks and Information Processing (ISSNIP …, 2010 | 78 | 2010 |
| Learning Markov Networks with Arithmetic Circuits D Lowd, A Rooshenas AISTATS'13, 2013 | 74 | 2013 |
| The Libra Toolkit for Probabilistic Models D Lowd, A Rooshenas Journal of Machine Learning Research 16, 2459-2463, 2015 | 37 | 2015 |
| Energy-Based Reranking: Improving Neural Machine Translation Using Energy-Based Models S Bhattacharyya, A Rooshenas, S Naskar, S Sun, M Iyyer, A McCallum ACL 2021, 2021 | 26 | 2021 |
| Discriminative Structure Learning of Arithmetic Circuits A Rooshenas, D Lowd AISTATS'16, 2016 | 23 | 2016 |
| Learning tractable graphical models using mixture of arithmetic circuits A Rooshenas, D Lowd Proceedings of the 17th AAAI Conference on Late-Breaking Developments in the …, 2013 | 9 | 2013 |
| Learning Compact Neural Networks Using Ordinary Differential Equations as Activation Functions MA Torkamani, P Wallis, S Shankar, A Rooshenas ICML Workshop on On-Device ML and Compact Deep Neural Networks (ODML-CDNNR2019), 2019 | 6 | 2019 |
| Search-Guided, Lightly-Supervised Training of Structured Prediction Energy Networks A Rooshenas, D Zhang, G Sharma, A McCallum NeurIPS'19, 2019 | 6 | 2019 |
| Training Structured Prediction Energy Networks with Indirect Supervision A Rooshenas, A Kamath, A McCallum HLT-NAACL 2018, 2018 | 5 | 2018 |
| Differential Equation Units: Learning Functional Forms of Activation Functions from Data MA Torkamani, S Shankar, A Rooshenas, P Wallis AAAI'20, 2020 | 2 | 2020 |
| Improved Training of Physics-Informed Neural Networks Using Energy-Based Priors: a Study on Electrical Impedance Tomography A Pokkunuru, A Rooshenas, T Strauss, A Abhishek, T Khan ICLR'23, 2023 | | 2023 |
| Learning Tractable Graphical Models A Rooshenas University of Oregon, 2017 | | 2017 |
| User Manual for Libra 1.1. 2d D Lowd, A Rooshenas | | 2015 |
| Supplementary Material for Discriminative Structure Learning of Arithmetic Circuits A Rooshenas, D Lowd | | |
| Supplementary Material for Learning Sum-Product Networks with Direct and Indirect Variable Interactions A Rooshenas, U EDU, D Lowd | | |
Daniel LowdAssociate Professor of Computer Science, University of OregonDirección de correo verificada de cs.uoregon.edu
