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ORCIDWei Deng 0002
Person information
- affiliation: Purdue University, West Lafayette, IN, USA
Other persons with the same name
- Wei Deng — disambiguation page
- Wei Deng 0001
![[0000-0002-6323-4539]](https://dblp.uni-trier.de./img/orcid-mark.12x12.png "0000-0002-6323-4539")
— Tsinghua University, Institute of Microelectronics, Beijing, China (and 2 more) - Wei Deng 0003 — outhwest University of Finance & Economics, China
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Journal Articles
- 2022
[j3]Wei Deng, Guang Lin, Faming Liang:
An adaptively weighted stochastic gradient MCMC algorithm for Monte Carlo simulation and global optimization. Stat. Comput. 32(4): 58 (2022)- 2021
- [j2]Yating Wang, Wei Deng, Guang Lin:
Bayesian sparse learning with preconditioned stochastic gradient MCMC and its applications. J. Comput. Phys. 432: 110134 (2021) - [j1]Yating Wang, Wei Deng, Guang Lin:
An adaptive Hessian approximated stochastic gradient MCMC method. J. Comput. Phys. 432: 110150 (2021)
Conference and Workshop Papers
- 2024
- [c12]Haoyang Zheng, Wei Deng, Christian Moya, Guang Lin:
Accelerating Approximate Thompson Sampling with Underdamped Langevin Monte Carlo. AISTATS 2024: 2611-2619 - [c11]Wei Deng, Weijian Luo, Yixin Tan, Marin Bilos, Yu Chen, Yuriy Nevmyvaka, Ricky T. Q. Chen:
Variational Schrödinger Diffusion Models. ICML 2024 - [c10]Haoyang Zheng, Hengrong Du, Qi Feng, Wei Deng, Guang Lin:
Constrained Exploration via Reflected Replica Exchange Stochastic Gradient Langevin Dynamics. ICML 2024 - 2023
- [c9]Wei Deng, Qian Zhang, Qi Feng, Faming Liang, Guang Lin:
Non-reversible Parallel Tempering for Deep Posterior Approximation. AAAI 2023: 7332-7339 - 2022
- [c8]Wei Deng, Siqi Liang, Botao Hao, Guang Lin, Faming Liang:
Interacting Contour Stochastic Gradient Langevin Dynamics. ICLR 2022 - 2021
- [c7]Wei Deng, Qi Feng, Georgios Karagiannis, Guang Lin, Faming Liang:
Accelerating Convergence of Replica Exchange Stochastic Gradient MCMC via Variance Reduction. ICLR 2021 - [c6]Botao Hao, Tor Lattimore, Wei Deng:
Information Directed Sampling for Sparse Linear Bandits. NeurIPS 2021: 16738-16750 - [c5]Wei Deng, Junwei Pan, Tian Zhou, Deguang Kong, Aaron Flores, Guang Lin:
DeepLight: Deep Lightweight Feature Interactions for Accelerating CTR Predictions in Ad Serving. WSDM 2021: 922-930 - 2020
- [c4]Wei Deng, Qi Feng, Liyao Gao, Faming Liang, Guang Lin:
Non-convex Learning via Replica Exchange Stochastic Gradient MCMC. ICML 2020: 2474-2483 - [c3]Wei Deng, Guang Lin, Faming Liang:
A Contour Stochastic Gradient Langevin Dynamics Algorithm for Simulations of Multi-modal Distributions. NeurIPS 2020 - 2019
- [c2]Wei Deng, Xiao Zhang, Faming Liang, Guang Lin:
An Adaptive Empirical Bayesian Method for Sparse Deep Learning. NeurIPS 2019: 5564-5574 - 2017
- [c1]Rongrong Zhang, Wei Deng, Yu Michael Zhu:
Using Deep Neural Networks to Automate Large Scale Statistical Analysis for Big Data Applications. ACML 2017: 311-326
Informal and Other Publications
- 2024
- [i17]Wei Deng, Yu Chen, Nicole Tianjiao Yang, Hengrong Du, Qi Feng, Ricky T. Q. Chen:
Reflected Schrödinger Bridge for Constrained Generative Modeling. CoRR abs/2401.03228 (2024) - [i16]Haoyang Zheng, Wei Deng, Christian Moya, Guang Lin:
Accelerating Approximate Thompson Sampling with Underdamped Langevin Monte Carlo. CoRR abs/2401.11665 (2024) - [i15]Wei Deng, Weijian Luo, Yixin Tan, Marin Bilos, Yu Chen, Yuriy Nevmyvaka, Ricky T. Q. Chen:
Variational Schrödinger Diffusion Models. CoRR abs/2405.04795 (2024) - [i14]Haoyang Zheng, Hengrong Du, Qi Feng, Wei Deng, Guang Lin:
Constrained Exploration via Reflected Replica Exchange Stochastic Gradient Langevin Dynamics. CoRR abs/2405.07839 (2024) - [i13]Yu Chen, Marin Bilos, Sarthak Mittal, Wei Deng, Kashif Rasul, Anderson Schneider:
Recurrent Interpolants for Probabilistic Time Series Prediction. CoRR abs/2409.11684 (2024) - 2022
- [i12]Wei Deng, Siqi Liang, Botao Hao, Guang Lin, Faming Liang:
Interacting Contour Stochastic Gradient Langevin Dynamics. CoRR abs/2202.09867 (2022) - [i11]Wei Deng, Qian Zhang, Qi Feng, Faming Liang, Guang Lin:
Non-reversible Parallel Tempering for Deep Posterior Approximation. CoRR abs/2211.10837 (2022) - 2021
- [i10]Botao Hao, Tor Lattimore, Wei Deng:
Information Directed Sampling for Sparse Linear Bandits. CoRR abs/2105.14267 (2021) - [i9]Wei Deng, Yi-An Ma, Zhao Song, Qian Zhang, Guang Lin:
On Convergence of Federated Averaging Langevin Dynamics. CoRR abs/2112.05120 (2021) - 2020
- [i8]Wei Deng, Junwei Pan, Tian Zhou, Aaron Flores, Guang Lin:
DeepLight: Deep Lightweight Feature Interactions for Accelerating CTR Predictions in Ad Serving. CoRR abs/2002.06987 (2020) - [i7]Yating Wang, Wei Deng, Guang Lin:
Bayesian Sparse learning with preconditioned stochastic gradient MCMC and its applications. CoRR abs/2006.16376 (2020) - [i6]Wei Deng, Qi Feng, Liyao Gao, Faming Liang, Guang Lin:
Non-convex Learning via Replica Exchange Stochastic Gradient MCMC. CoRR abs/2008.05367 (2020) - [i5]Wei Deng, Qi Feng, Georgios Karagiannis, Guang Lin, Faming Liang:
Accelerating Convergence of Replica Exchange Stochastic Gradient MCMC via Variance Reduction. CoRR abs/2010.01084 (2020) - [i4]Yating Wang, Wei Deng, Guang Lin:
An adaptive Hessian approximated stochastic gradient MCMC method. CoRR abs/2010.01384 (2020) - [i3]Wei Deng, Guang Lin, Faming Liang:
A Contour Stochastic Gradient Langevin Dynamics Algorithm for Simulations of Multi-modal Distributions. CoRR abs/2010.09800 (2020) - 2019
- [i2]Wei Deng, Xiao Zhang, Faming Liang, Guang Lin:
An Adaptive Empirical Bayesian Method for Sparse Deep Learning. CoRR abs/1910.10791 (2019) - 2017
- [i1]Rongrong Zhang, Wei Deng, Yu Michael Zhu:
Using Deep Neural Networks to Automate Large Scale Statistical Analysis for Big Data Applications. CoRR abs/1708.03027 (2017)
Coauthor Index
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