Hu, Edward J

11 publications

ICLR 2024 Amortizing Intractable Inference in Large Language Models Edward J Hu, Moksh Jain, Eric Elmoznino, Younesse Kaddar, Guillaume Lajoie, Yoshua Bengio, Nikolay Malkin

ICML 2023 Differentiable Tree Operations Promote Compositional Generalization Paul Soulos, Edward J Hu, Kate Mccurdy, Yunmo Chen, Roland Fernandez, Paul Smolensky, Jianfeng Gao

ICMLW 2023 Differentiable Tree Operations Promote Compositional Generalization Paul Soulos, Edward J Hu, Kate McCurdy, Yunmo Chen, Roland Fernandez, Paul Smolensky, Jianfeng Gao

JMLR 2023 GFlowNet Foundations Yoshua Bengio, Salem Lahlou, Tristan Deleu, Edward J. Hu, Mo Tiwari, Emmanuel Bengio

ICML 2023 GFlowNet-EM for Learning Compositional Latent Variable Models Edward J Hu, Nikolay Malkin, Moksh Jain, Katie E Everett, Alexandros Graikos, Yoshua Bengio

ICLR 2023 GFlowNets and Variational Inference Nikolay Malkin, Salem Lahlou, Tristan Deleu, Xu Ji, Edward J Hu, Katie E Everett, Dinghuai Zhang, Yoshua Bengio

ICMLW 2023 GFlowNets for Causal Discovery: An Overview Dragos Cristian Manta, Edward J Hu, Yoshua Bengio

ICMLW 2023 GFlowNets for Causal Discovery: An Overview Dragos Cristian Manta, Edward J Hu, Yoshua Bengio

ICLR 2022 Efficient Computation of Deep Nonlinear Infinite-Width Neural Networks That Learn Features Greg Yang, Michael Santacroce, Edward J Hu

ICLR 2022 LoRA: Low-Rank Adaptation of Large Language Models Edward J Hu, Yelong Shen, Phillip Wallis, Zeyuan Allen-Zhu, Yuanzhi Li, Shean Wang, Lu Wang, Weizhu Chen

ICML 2021 Tensor Programs IV: Feature Learning in Infinite-Width Neural Networks Greg Yang, Edward J. Hu