Jinlin Lai

14 papers A* 2A 1Journal 8Unranked 3
YearRankTypeTitle / Venue / Authors
2025 J jnl
Active Measurement: Efficient Estimation at Scale.
CoRR
Max Hamilton, Jinlin Lai, Wenlong Zhao, Subhransu Maji, Daniel Sheldon
2024 A* conf
Hamiltonian Monte Carlo Inference of Marginalized Linear Mixed-Effects Models.
NeurIPS
Jinlin Lai, Justin Domke, Daniel R. Sheldon
2024 J jnl
Hamiltonian Monte Carlo Inference of Marginalized Linear Mixed-Effects Models.
CoRR
Jinlin Lai, Daniel Sheldon, Justin Domke
2024 — conf
Outdoor Scene Relighting with Diffusion Models.
ICPR (6)
Jinlin Lai, Anustup Choudhury, Guan-Ming Su
2024 J jnl
Predictive variational inference: Learn the predictively optimal posterior distribution.
CoRR
Jinlin Lai, Yuling Yao
2024 J jnl
Quasi-random Multi-Sample Inference for Large Language Models.
CoRR
Aditya Parashar, Aditya Vikram Singh, Avinash Amballa, Jinlin Lai, Benjamin Rozonoyer
2023 J jnl
Automatically Marginalized MCMC in Probabilistic Programming.
CoRR
Jinlin Lai, Javier Burroni, Hui Guan, Daniel Sheldon
2023 A* conf
Automatically marginalized MCMC in probabilistic programming.
ICML
Jinlin Lai, Javier Burroni, Hui Guan, Daniel Sheldon
2023 — conf
Efficient Semi-Supervised Segmentation of Medical Images with RESA-Enhanced U-Net.
IC-NIDC
Saijun Nie, Tianyu Xiao, Jinlin Lai, Yuandong Li, Siye Wang
2022 A conf
Variational Marginal Particle Filters.
AISTATS
Jinlin Lai, Justin Domke, Daniel Sheldon
2021 J jnl
Variational Marginal Particle Filters.
CoRR
Jinlin Lai, Daniel Sheldon, Justin Domke
2020 J jnl
Optimal Mixture Weights for Off-Policy Evaluation with Multiple Behavior Policies.
CoRR
Jinlin Lai, Lixin Zou, Jiaxing Song
2020 — conf
Shallow VAEs with RealNVP Prior can Perform as Well as Deep Hierarchical VAEs.
ICONIP (5)
Haowen Xu, Wenxiao Chen, Jinlin Lai, Zhihan Li, Youjian Zhao, Dan Pei
2019 J jnl
On the Necessity and Effectiveness of Learning the Prior of Variational Auto-Encoder.
CoRR
Haowen Xu, Wenxiao Chen, Jinlin Lai, Zhihan Li, Youjian Zhao, Dan Pei