Nijkamp, Erik

10 publications

ICLR 2023 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

NeurIPSW 2022 Generating High Fidelity Synthetic Data via Coreset Selection and Entropic Regularization Omead Pooladzandi, Pasha Khosravi, Erik Nijkamp, Baharan Mirzasoleiman

NeurIPS 2022 Learning Probabilistic Models from Generator Latent Spaces with Hat EBM Mitch Hill, Erik Nijkamp, Jonathan Mitchell, Bo Pang, Song-Chun Zhu

ICLR 2022 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

NeurIPS 2020 Learning Latent Space Energy-Based Prior Model Bo Pang, Tian Han, Erik Nijkamp, Song-Chun Zhu, Ying Nian Wu

ECCV 2020 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

AAAI 2020 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

NeurIPSW 2020 Semi-Supervised Learning by Latent Space Energy-Based Model of Symbol-Vector Coupling Bo Pang, Erik Nijkamp, Jiali Cui, Tian Han, Ying Nian Wu

NeurIPS 2019 Learning Non-Convergent Non-Persistent Short-Run MCMC Toward Energy-Based Model Erik Nijkamp, Mitch Hill, Song-Chun Zhu, Ying Nian Wu

CVPR 2017 Generative Hierarchical Learning of Sparse FRAME Models Jianwen Xie, Yifei Xu, Erik Nijkamp, Ying Nian Wu, Song-Chun Zhu