Wei Deng - RankMe

46 papers A* 10A 6C 1Journal 29

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Generalized Discrete Diffusion with Self-Correction. CoRR Linxuan Wang, Ziyi Wang, Yikun Bai, Wei Deng, Guang Lin, Qifan Song
2025	J	`jnl`	Bayesian Federated Learning with Hamiltonian Monte Carlo: Algorithm and Theory. J. Comput. Graph. Stat. Jiajun Liang, Qian Zhang, Wei Deng, Qifan Song, Guang Lin
2025	J	`jnl`	Improving Reasoning for Diffusion Language Models via Group Diffusion Policy Optimization. CoRR Kevin Rojas, Jiahe Lin, Kashif Rasul, Anderson Schneider, Yuriy Nevmyvaka, Molei Tao, Wei Deng
2025	A	`conf`	Optimal Stochastic Trace Estimation in Generative Modeling. AISTATS Xinyang Liu, Hengrong Du, Wei Deng, Ruqi Zhang
2025	J	`jnl`	Optimal Stochastic Trace Estimation in Generative Modeling. CoRR Xinyang Liu, Hengrong Du, Wei Deng, Ruqi Zhang
2025	J	`jnl`	Rethinking Langevin Thompson Sampling from A Stochastic Approximation Perspective. CoRR Weixin Wang, Haoyang Zheng, Guang Lin, Wei Deng, Pan Xu
2025	J	`jnl`	Ultra-Fast Language Generation via Discrete Diffusion Divergence Instruct. CoRR Haoyang Zheng, Xinyang Liu, Cindy Xiangrui Kong, Nan Jiang, Zheyuan Hu, Weijian Luo, Wei Deng, Guang Lin
2025	A	`conf`	Variational Schrödinger Momentum Diffusion. AISTATS Kevin Rojas, Yixin Tan, Molei Tao, Yuriy Nevmyvaka, Wei Deng
2025	J	`jnl`	Variational Schrödinger Momentum Diffusion. CoRR Kevin Rojas, Yixin Tan, Molei Tao, Yuriy Nevmyvaka, Wei Deng
2024	A	`conf`	Accelerating Approximate Thompson Sampling with Underdamped Langevin Monte Carlo. AISTATS Haoyang Zheng, Wei Deng, Christian Moya, Guang Lin
2024	J	`jnl`	Accelerating Approximate Thompson Sampling with Underdamped Langevin Monte Carlo. CoRR Haoyang Zheng, Wei Deng, Christian Moya, Guang Lin
2024	J	`jnl`	Bayesian Federated Learning with Hamiltonian Monte Carlo: Algorithm and Theory. CoRR Jiajun Liang, Qian Zhang, Wei Deng, Qifan Song, Guang Lin
2024	A*	`conf`	Constrained Exploration via Reflected Replica Exchange Stochastic Gradient Langevin Dynamics. ICML Haoyang Zheng, Hengrong Du, Qi Feng, Wei Deng, Guang Lin
2024	J	`jnl`	Constrained Exploration via Reflected Replica Exchange Stochastic Gradient Langevin Dynamics. CoRR Haoyang Zheng, Hengrong Du, Qi Feng, Wei Deng, Guang Lin
2024	A	`conf`	On Convergence of Federated Averaging Langevin Dynamics. UAI Wei Deng, Qian Zhang, Yian Ma, Zhao Song, Guang Lin
2024	J	`jnl`	Recurrent Interpolants for Probabilistic Time Series Prediction. CoRR Yu Chen, Marin Bilos, Sarthak Mittal, Wei Deng, Kashif Rasul, Anderson Schneider
2024	A	`conf`	Reflected Schrödinger Bridge for Constrained Generative Modeling. UAI Wei Deng, Yu Chen, Nicole Tianjiao Yang, Hengrong Du, Qi Feng, Ricky Tian Qi Chen
2024	J	`jnl`	Reflected Schrödinger Bridge for Constrained Generative Modeling. CoRR Wei Deng, Yu Chen, Nicole Tianjiao Yang, Hengrong Du, Qi Feng, Ricky T. Q. Chen
2024	A*	`conf`	Variational Schrödinger Diffusion Models. ICML Wei Deng, Weijian Luo, Yixin Tan, Marin Bilos, Yu Chen, Yuriy Nevmyvaka, Ricky T. Q. Chen
2024	J	`jnl`	Variational Schrödinger Diffusion Models. CoRR Wei Deng, Weijian Luo, Yixin Tan, Marin Bilos, Yu Chen, Yuriy Nevmyvaka, Ricky T. Q. Chen
2023	A*	`conf`	Non-reversible Parallel Tempering for Deep Posterior Approximation. AAAI Wei Deng, Qian Zhang, Qi Feng, Faming Liang, Guang Lin
2023	A*	`conf`	Provably Convergent Schrödinger Bridge with Applications to Probabilistic Time Series Imputation. ICML Yu Chen, Wei Deng, Shikai Fang, Fengpei Li, Nicole Tianjiao Yang, Yikai Zhang, Kashif Rasul, Shandian Zhe, Anderson Schneider, Yuriy Nevmyvaka
2023	J	`jnl`	Provably Convergent Schrödinger Bridge with Applications to Probabilistic Time Series Imputation. CoRR Yu Chen, Wei Deng, Shikai Fang, Fengpei Li, Nicole Tianjiao Yang, Yikai Zhang, Kashif Rasul, Shandian Zhe, Anderson Schneider, Yuriy Nevmyvaka
2022	J	`jnl`	An adaptively weighted stochastic gradient MCMC algorithm for Monte Carlo simulation and global optimization. Stat. Comput. Wei Deng, Guang Lin, Faming Liang
2022	A*	`conf`	Interacting Contour Stochastic Gradient Langevin Dynamics. ICLR Wei Deng, Siqi Liang, Botao Hao, Guang Lin, Faming Liang
2022	J	`jnl`	Interacting Contour Stochastic Gradient Langevin Dynamics. CoRR Wei Deng, Siqi Liang, Botao Hao, Guang Lin, Faming Liang
2022	J	`jnl`	Non-reversible Parallel Tempering for Deep Posterior Approximation. CoRR Wei Deng, Qian Zhang, Qi Feng, Faming Liang, Guang Lin
2021	A*	`conf`	Accelerating Convergence of Replica Exchange Stochastic Gradient MCMC via Variance Reduction. ICLR Wei Deng, Qi Feng, Georgios Karagiannis, Guang Lin, Faming Liang
2021	J	`jnl`	An adaptive Hessian approximated stochastic gradient MCMC method. J. Comput. Phys. Yating Wang, Wei Deng, Guang Lin
2021	J	`jnl`	Bayesian sparse learning with preconditioned stochastic gradient MCMC and its applications. J. Comput. Phys. Yating Wang, Wei Deng, Guang Lin
2021	A	`conf`	DeepLight: Deep Lightweight Feature Interactions for Accelerating CTR Predictions in Ad Serving. WSDM Wei Deng, Junwei Pan, Tian Zhou, Deguang Kong, Aaron Flores, Guang Lin
2021	A*	`conf`	Information Directed Sampling for Sparse Linear Bandits. NeurIPS Botao Hao, Tor Lattimore, Wei Deng
2021	J	`jnl`	Information Directed Sampling for Sparse Linear Bandits. CoRR Botao Hao, Tor Lattimore, Wei Deng
2021	J	`jnl`	On Convergence of Federated Averaging Langevin Dynamics. CoRR Wei Deng, Yi-An Ma, Zhao Song, Qian Zhang, Guang Lin
2020	A*	`conf`	A Contour Stochastic Gradient Langevin Dynamics Algorithm for Simulations of Multi-modal Distributions. NeurIPS Wei Deng, Guang Lin, Faming Liang
2020	J	`jnl`	A Contour Stochastic Gradient Langevin Dynamics Algorithm for Simulations of Multi-modal Distributions. CoRR Wei Deng, Guang Lin, Faming Liang
2020	J	`jnl`	Accelerating Convergence of Replica Exchange Stochastic Gradient MCMC via Variance Reduction. CoRR Wei Deng, Qi Feng, Georgios Karagiannis, Guang Lin, Faming Liang
2020	J	`jnl`	An adaptive Hessian approximated stochastic gradient MCMC method. CoRR Yating Wang, Wei Deng, Guang Lin
2020	J	`jnl`	Bayesian Sparse learning with preconditioned stochastic gradient MCMC and its applications. CoRR Yating Wang, Wei Deng, Guang Lin
2020	J	`jnl`	DeepLight: Deep Lightweight Feature Interactions for Accelerating CTR Predictions in Ad Serving. CoRR Wei Deng, Junwei Pan, Tian Zhou, Aaron Flores, Guang Lin
2020	A*	`conf`	Non-convex Learning via Replica Exchange Stochastic Gradient MCMC. ICML Wei Deng, Qi Feng, Liyao Gao, Faming Liang, Guang Lin
2020	J	`jnl`	Non-convex Learning via Replica Exchange Stochastic Gradient MCMC. CoRR Wei Deng, Qi Feng, Liyao Gao, Faming Liang, Guang Lin
2019	A*	`conf`	An Adaptive Empirical Bayesian Method for Sparse Deep Learning. NeurIPS Wei Deng, Xiao Zhang, Faming Liang, Guang Lin
2019	J	`jnl`	An Adaptive Empirical Bayesian Method for Sparse Deep Learning. CoRR Wei Deng, Xiao Zhang, Faming Liang, Guang Lin
2017	C	`conf`	Using Deep Neural Networks to Automate Large Scale Statistical Analysis for Big Data Applications. ACML Rongrong Zhang, Wei Deng, Yu Michael Zhu
2017	J	`jnl`	Using Deep Neural Networks to Automate Large Scale Statistical Analysis for Big Data Applications. CoRR Rongrong Zhang, Wei Deng, Yu Michael Zhu