Codegen: An open large language model for code with multi-turn program synthesis E Nijkamp, B Pang, H Hayashi, L Tu, H Wang, Y Zhou, S Savarese, ... arXiv preprint arXiv:2203.13474, 2022 | 977 | 2022 |
Large-scale matrix factorization with distributed stochastic gradient descent R Gemulla, E Nijkamp, PJ Haas, Y Sismanis Proceedings of the 17th ACM SIGKDD international conference on Knowledge …, 2011 | 882 | 2011 |
Deep learning with tensorflow: A review B Pang, E Nijkamp, YN Wu Journal of Educational and Behavioral Statistics 45 (2), 227-248, 2020 | 496 | 2020 |
Learning non-convergent non-persistent short-run mcmc toward energy-based model E Nijkamp, M Hill, SC Zhu, YN Wu Advances in Neural Information Processing Systems 32, 2019 | 265 | 2019 |
Progen2: exploring the boundaries of protein language models E Nijkamp, JA Ruffolo, EN Weinstein, N Naik, A Madani Cell systems 14 (11), 968-978. e3, 2023 | 252 | 2023 |
On the anatomy of mcmc-based maximum likelihood learning of energy-based models E Nijkamp, M Hill, T Han, SC Zhu, YN Wu Proceedings of the AAAI Conference on Artificial Intelligence 34 (04), 5272-5280, 2020 | 180 | 2020 |
Codegen2: Lessons for training llms on programming and natural languages E Nijkamp, H Hayashi, C Xiong, S Savarese, Y Zhou arXiv preprint arXiv:2305.02309, 2023 | 174 | 2023 |
A conversational paradigm for program synthesis E Nijkamp, B Pang, H Hayashi, L Tu, H Wang, Y Zhou, S Savarese, ... arXiv preprint arXiv:2203.13474 30, 2022 | 155 | 2022 |
Learning latent space energy-based prior model B Pang, T Han, E Nijkamp, SC Zhu, YN Wu Advances in Neural Information Processing Systems 33, 21994-22008, 2020 | 147 | 2020 |
Flow contrastive estimation of energy-based models R Gao, E Nijkamp, DP Kingma, Z Xu, AM Dai, YN Wu Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2020 | 125 | 2020 |
Towards holistic and automatic evaluation of open-domain dialogue generation B Pang, E Nijkamp, W Han, L Zhou, Y Liu, K Tu Proceedings of the 58th annual meeting of the association for computational …, 2020 | 84 | 2020 |
MapReduce and PACT-comparing data parallel programming models A Alexandrov, S Ewen, M Heimel, F Hueske, O Kao, V Markl, E Nijkamp, ... Gesellschaft für Informatik eV, 2011 | 78 | 2011 |
Massively parallel data analysis with pacts on nephele A Alexandrov, M Heimel, V Markl, D Battré, F Hueske, E Nijkamp, S Ewen, ... Proceedings of the VLDB Endowment 3 (1-2), 1625-1628, 2010 | 73 | 2010 |
Divergence triangle for joint training of generator model, energy-based model, and inferential model T Han, E Nijkamp, X Fang, M Hill, SC Zhu, YN Wu Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2019 | 72 | 2019 |
Scaling dynamic authority-based search using materialized subgraphs A Balmin, H Hwang, E Nijkamp, B Reinwald US Patent 9,171,077, 2015 | 64 | 2015 |
Long document summarization with top-down and bottom-up inference B Pang, E Nijkamp, W Kryściński, S Savarese, Y Zhou, C Xiong arXiv preprint arXiv:2203.07586, 2022 | 54 | 2022 |
Learning multi-layer latent variable model via variational optimization of short run mcmc for approximate inference E Nijkamp, B Pang, T Han, L Zhou, SC Zhu, YN Wu Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23 …, 2020 | 52 | 2020 |
Joint training of variational auto-encoder and latent energy-based model T Han, E Nijkamp, L Zhou, B Pang, SC Zhu, YN Wu Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2020 | 52 | 2020 |
Scaling dynamic authority-based search using materialized subgraphs A Balmin, H Hwang, E Nijkamp, B Reinwald US Patent 10,521,435, 2019 | 39 | 2019 |
Xgen-7b technical report E Nijkamp, T Xie, H Hayashi, B Pang, C Xia, C Xing, J Vig, S Yavuz, ... arXiv preprint arXiv:2309.03450, 2023 | 26 | 2023 |