Xuechen Li
13 papers · 2018–2024 · 6 venues · across top CS/AI venues
Authors are matched by name, so researchers who share a name ("Yang Liu", "Wei Wang") appear as a single profile and their paper counts, venues and achievements are combined. How identity is handled.
Achievements
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🌉 Interdisciplinary Bridge · Bronze 🗺️ Taxonomy Completionist (24) 🌍 Conference Polyglot · Silver 🐣 Hot Topic Early Bird 🏃 Academic Marathon · Sprint
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The Questioner
(2)
🔥
Unstoppable · Bronze
💎
Century Club · Bronze
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Keyword Collector
(56)
Top co-authors
Research topics
Machine Learning
(10)
Artificial Intelligence
(6)
Optimization & Theory · Machine Learning
(6)
Deep Learning
(4)
Application Areas
(4)
Core AI
(3)
Natural Language Processing
(2)
Bayesian & Probabilistic · Artificial Intelligence
(2)
Core Methods
(2)
Generation
(2)
Optimization & Theory · Deep Learning
(2)
Mathematics & Optimization
(1)
Security & Privacy
(1)
Architectures
(1)
Bayesian & Probabilistic · Machine Learning
(1)
Keywords
differential privacy
(4)
large language model
(3)
stochastic differential equation
(3)
variational autoencoder
(2)
stochastic variational inference
(2)
private fine-tuning
(2)
markov chain monte carlo
(1)
deep learning
(1)
reinforcement learning
(1)
natural gradient descent
(1)
gradient computation
(1)
excess risk bound
(1)
high-dimensional optimization
(1)
posterior approximation
(1)
probabilistic prediction
(1)
intellectual property
(1)
disentangled representation
(1)
latent variable model
(1)
mutual information
(1)
amortized inference
(1)
Papers
Linguistic Calibration of Long-Form Generations
ICML 2024
Exploring the Limits of Differentially Private Deep Learning with Group-wise Clipping
ICLR 2023
Foundation Models and Fair Use
JMLR 2023
Synthetic Text Generation with Differential Privacy: A Simple and Practical Recipe
ACL 2023
Infinitely Deep Bayesian Neural Networks with Stochastic Differential Equations
AISTATS 2022
Large Language Models Can Be Strong Differentially Private Learners
ICLR 2022
When Does Differentially Private Learning Not Suffer in High Dimensions?
NeurIPS 2022
Neural SDEs as Infinite-Dimensional GANs
ICML 2021
When does preconditioning help or hurt generalization?
ICLR 2021
Scalable Gradients for Stochastic Differential Equations
AISTATS 2020
Stochastic Runge-Kutta Accelerates Langevin Monte Carlo and Beyond
NeurIPS 2019
Inference Suboptimality in Variational Autoencoders
ICML 2018
Isolating Sources of Disentanglement in Variational Autoencoders
NeurIPS 2018