| 2023 | EACL | Long Document Summarization with Top-down and Bottom-up Inference. | Bo Pang, Erik Nijkamp, Wojciech Kryscinski, Silvio Savarese, Yingbo Zhou, Caiming Xiong |
| 2023 | ICLR | CodeGen: An Open Large Language Model for Code with Multi-Turn Program Synthesis. | Erik Nijkamp, Bo Pang, Hiroaki Hayashi, Lifu Tu, Huan Wang, Yingbo Zhou, Silvio Savarese, Caiming Xiong |
| 2022 | ICLR | MCMC Should Mix: Learning Energy-Based Model with Neural Transport Latent Space MCMC. | Erik Nijkamp, Ruiqi Gao, Pavel Sountsov, Srinivas Vasudevan, Bo Pang, Song-Chun Zhu, Ying Nian Wu |
| 2021 | EACL | Generative Text Modeling through Short Run Inference. | Bo Pang, Erik Nijkamp, Tian Han, Ying Nian Wu |
| 2021 | NAACL | SCRIPT: Self-Critic PreTraining of Transformers. | Erik Nijkamp, Bo Pang, Ying Nian Wu, Caiming Xiong |
| 2020 | AAAI | On the Anatomy of MCMC-Based Maximum Likelihood Learning of Energy-Based Models. | Erik Nijkamp, Mitch Hill, Tian Han, Song-Chun Zhu, Ying Nian Wu |
| 2020 | ACL | Towards Holistic and Automatic Evaluation of Open-Domain Dialogue Generation. | Bo Pang, Erik Nijkamp, Wenjuan Han, Linqi Zhou, Yixian Liu, Kewei Tu |
| 2020 | CVPR | Joint Training of Variational Auto-Encoder and Latent Energy-Based Model. | Tian Han, Erik Nijkamp, Linqi Zhou, Bo Pang, Song-Chun Zhu, Ying Nian Wu |
| 2020 | CVPR | Flow Contrastive Estimation of Energy-Based Models. | Ruiqi Gao, Erik Nijkamp, Diederik P. Kingma, Zhen Xu, Andrew M. Dai, Ying Nian Wu |
| 2020 | ECCV | Learning Multi-layer Latent Variable Model via Variational Optimization of Short Run MCMC for Approximate Inference. | Erik Nijkamp, Bo Pang, Tian Han, Linqi Zhou, Song-Chun Zhu, Ying Nian Wu |
| 2019 | CVPR | Divergence Triangle for Joint Training of Generator Model, Energy-Based Model, and Inferential Model. | Tian Han, Erik Nijkamp, Xiaolin Fang, Mitch Hill, Song-Chun Zhu, Ying Nian Wu |
| 2017 | CVPR | Generative Hierarchical Learning of Sparse FRAME Models. | Jianwen Xie, Yifei Xu, Erik Nijkamp, Ying Nian Wu, Song-Chun Zhu |
| 2011 | BTW | MapReduce and PACT - Comparing Data Parallel Programming Models. | Alexander Alexandrov, Stephan Ewen, Max Heimel, Fabian Hueske, Odej Kao, Volker Markl, Erik Nijkamp, Daniel Warneke |
| 2011 | KDD | Large-scale matrix factorization with distributed stochastic gradient descent. | Rainer Gemulla, Erik Nijkamp, Peter J. Haas, Yannis Sismanis |
| 2009 | BTW | Value Demonstration of Embedded Analytics for Front Office Applications. | Erik Nijkamp, Martin A. Oberhofer, Albert Maier |
| 2009 | BTW | Embedded Analytics in Front Office Applications. | Martin A. Oberhofer, Erik Nijkamp |
| 2009 | ICDE | BinRank: Scaling Dynamic Authority-Based Search Using Materialized SubGraphs. | Heasoo Hwang, Andrey Balmin, Berthold Reinwald, Erik Nijkamp |