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Ruqi Zhang
Ruqi Zhang
Assistant Professor of Computer Science, Purdue University
Verified email at purdue.edu - Homepage
Title
Cited by
Cited by
Year
Cyclical stochastic gradient MCMC for Bayesian deep learning
R Zhang, C Li, J Zhang, C Chen, AG Wilson
International Conference on Learning Representations (ICLR), 2019
2802019
A Langevin-like Sampler for Discrete Distributions
R Zhang, X Liu, Q Liu
International Conference on Machine Learning, 26375-26396, 2022
222022
Asymptotically optimal exact minibatch metropolis-hastings
R Zhang, AF Cooper, CM De Sa
Advances in Neural Information Processing Systems 33, 19500-19510, 2020
182020
AMAGOLD: Amortized Metropolis adjustment for efficient stochastic gradient MCMC
R Zhang, AF Cooper, C De Sa
International Conference on Artificial Intelligence and Statistics, 2142-2152, 2020
172020
Large Scale Sparse Clustering.
R Zhang, Z Lu
IJCAI, 2336-2342, 2016
152016
Low-Precision Stochastic Gradient Langevin Dynamics
R Zhang, AG Wilson, C De Sa
International Conference on Machine Learning, 26624-26644, 2022
122022
Poisson-Minibatching for Gibbs Sampling with Convergence Rate Guarantees
R Zhang, CM De Sa
Advances in Neural Information Processing Systems, 4922-4931, 2019
112019
Meta-Learning Divergences for Variational Inference
R Zhang, Y Li, C De Sa, S Devlin, C Zhang
International Conference on Artificial Intelligence and Statistics, 4024-4032, 2021
72021
Calibrating the Rigged Lottery: Making All Tickets Reliable
B Lei, R Zhang, D Xu, B Mallick
arXiv preprint arXiv:2302.09369, 2023
62023
Sampling in Constrained Domains with Orthogonal-Space Variational Gradient Descent
R Zhang, Q Liu, X Tong
Advances in Neural Information Processing Systems 35, 37108-37120, 2022
62022
Balance is essence: Accelerating sparse training via adaptive gradient correction
B Lei, D Xu, R Zhang, S He, B Mallick
Conference on Parsimony and Learning, 341-378, 2024
42024
Rethinking data distillation: Do not overlook calibration
D Zhu, B Lei, J Zhang, Y Fang, Y Xie, R Zhang, D Xu
Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2023
42023
DP-Fast MH: Private, fast, and accurate Metropolis-Hastings for large-scale Bayesian inference
W Zhang, R Zhang
International Conference on Machine Learning, 41847-41860, 2023
22023
Discs: A benchmark for discrete sampling
K Goshvadi, H Sun, X Liu, A Nova, R Zhang, W Grathwohl, D Schuurmans, ...
Advances in Neural Information Processing Systems 36, 2024
12024
Position Paper: Bayesian Deep Learning in the Age of Large-Scale AI
T Papamarkou, M Skoularidou, K Palla, L Aitchison, J Arbel, D Dunson, ...
arXiv preprint arXiv:2402.00809, 2024
12024
Training Bayesian Neural Networks with Sparse Subspace Variational Inference
J Li, Z Miao, Q Qiu, R Zhang
Workshop on Advancing Neural Network Training: Computational Efficiency …, 2023
12023
Analysis of Climate Campaigns on Social Media using Bayesian Model Averaging
T Islam, R Zhang, D Goldwasser
Proceedings of the 2023 AAAI/ACM Conference on AI, Ethics, and Society, 15-25, 2023
12023
Efficient Informed Proposals for Discrete Distributions via Newton’s Series Approximation
Y Xiang, D Zhu, B Lei, D Xu, R Zhang
International Conference on Artificial Intelligence and Statistics, 7288-7310, 2023
12023
Gradient-based Discrete Sampling with Automatic Cyclical Scheduling
P Pynadath, R Bhattacharya, A Hariharan, R Zhang
arXiv preprint arXiv:2402.17699, 2024
2024
GAD-EBM: Graph Anomaly Detection using Energy-Based Models
A Roy, J Shu, O Elshocht, J Smeets, R Zhang, P Li
NeurIPS 2023 Workshop: New Frontiers in Graph Learning, 2023
2023
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