Ruqi Zhang
28 papers · 2016–2026 · 10 venues · across top CS/AI venues
This profile combines several different researchers. Authors are keyed by name, and this name's papers fall into 12 separate collaboration groups - the largest holds only 25% of them. Pick the group below that matches the researcher you mean. How a shared name is split.
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Which Ruqi Zhang?
6 groups of papers that share co-authors internally but none with each other - each most likely a different researcher. Pick one to see its papers.
with Andrew Gordon Wilson, Christopher De Sa, Yingzhen Li
7 papers
· 2019–2024
· ICML, AISTATS, NeurIPS
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Position: Bayesian Deep Learning is Needed in the Age of Large-Scale AI
ICML 2024
Low-Precision Stochastic Gradient Langevin Dynamics
ICML 2022
Meta-Learning Divergences for Variational Inference
AISTATS 2021
AMAGOLD: Amortized Metropolis Adjustment for Efficient Stochastic Gradient MCMC
AISTATS 2020
Asymptotically Optimal Exact Minibatch Metropolis-Hastings
NeurIPS 2020
Cyclical Stochastic Gradient MCMC for Bayesian Deep Learning
ICLR 2020
Poisson-Minibatching for Gibbs Sampling with Convergence Rate Guarantees
NeurIPS 2019
6 papers whose co-authors appear nowhere else under this name
Gradient-Guided Reward Optimization for Inference-time Alignment
UAI 2026
CoT-UQ: Improving Response-wise Uncertainty Quantification in LLMs with Chain-of-Thought
ACL 2025
Scalable and Efficient Probabilistic Inference for Bayesian Deep Learning and Generative Modeling
AAAI 2025
Training Bayesian Neural Networks with Sparse Subspace Variational Inference
ICLR 2024
DP-Fast MH: Private, Fast, and Accurate Metropolis-Hastings for Large-Scale Bayesian Inference
ICML 2023
Large Scale Sparse Clustering
IJCAI 2016