Xuechen Li | DeepAI

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Featured Co-authors

Xin Li
301 publications
Percy Liang
165 publications
Ce Zhang
133 publications
Christopher Ré
125 publications
Jue Wang
107 publications
Alois Knoll
95 publications
Tianyi Zhang
86 publications
Taiji Suzuki
84 publications
Christopher D. Manning
79 publications
Dan Jurafsky
77 publications
Ion Stoica
74 publications

∙ 08/10/2023

TCSloT: Text Guided 3D Context and Slope Aware Triple Network for Dental Implant Position Prediction

In implant prosthesis treatment, the surgical guide of implant is used t...

0 Xinquan Yang, et al. ∙

∙ 06/26/2023

TCEIP: Text Condition Embedded Regression Network for Dental Implant Position Prediction

When deep neural network has been proposed to assist the dentist in desi...

0 Xinquan Yang, et al. ∙

∙ 05/17/2023

Two-Stream Regression Network for Dental Implant Position Prediction

In implant prosthesis treatment, the design of surgical guide requires l...

0 Xinquan Yang, et al. ∙

∙ 03/28/2023

Foundation Models and Fair Use

Existing foundation models are trained on copyrighted material. Deployin...

0 Peter Henderson, et al. ∙

∙ 02/11/2023

Exploiting Programmatic Behavior of LLMs: Dual-Use Through Standard Security Attacks

Recent advances in instruction-following large language models (LLMs) ha...

0 Daniel Kang, et al. ∙

∙ 11/16/2022

Holistic Evaluation of Language Models

Language models (LMs) are becoming the foundation for almost all major l...

21 Percy Liang, et al. ∙

∙ 10/29/2022

ImplantFormer: Vision Transformer based Implant Position Regression Using Dental CBCT Data

Implant prosthesis is the most optimum treatment of dentition defect or ...

0 Xinquan Yang, et al. ∙

∙ 10/25/2022

Synthetic Text Generation with Differential Privacy: A Simple and Practical Recipe

Privacy concerns have attracted increasing attention in data-driven prod...

0 Xiang Yue, et al. ∙

∙ 10/15/2022

A Closer Look at the Calibration of Differentially Private Learners

We systematically study the calibration of classifiers trained with diff...

0 Hanlin Zhang, et al. ∙

∙ 08/07/2022

Sample hardness based gradient loss for long-tailed cervical cell detection

Due to the difficulty of cancer samples collection and annotation, cervi...

0 Minmin Liu, et al. ∙

∙ 07/01/2022

When Does Differentially Private Learning Not Suffer in High Dimensions?

Large pretrained models can be privately fine-tuned to achieve performan...

0 Xuechen Li, et al. ∙

∙ 10/12/2021

Large Language Models Can Be Strong Differentially Private Learners

Differentially Private (DP) learning has seen limited success for buildi...

0 Xuechen Li, et al. ∙

∙ 06/23/2021

Learning from Pseudo Lesion: A Self-supervised Framework for COVID-19 Diagnosis

The Coronavirus disease 2019 (COVID-19) has rapidly spread all over the ...

0 Zhongliang Li, et al. ∙

∙ 05/28/2021

Learning to Extend Program Graphs to Work-in-Progress Code

Source code spends most of its time in a broken or incomplete state duri...

0 Xuechen Li, et al. ∙

∙ 05/27/2021

Efficient and Accurate Gradients for Neural SDEs

Neural SDEs combine many of the best qualities of both RNNs and SDEs, an...

4 Patrick Kidger, et al. ∙

∙ 02/12/2021

Infinitely Deep Bayesian Neural Networks with Stochastic Differential Equations

We perform scalable approximate inference in a recently-proposed family ...

24 Winnie Xu, et al. ∙

∙ 02/06/2021

Neural SDEs as Infinite-Dimensional GANs

Stochastic differential equations (SDEs) are a staple of mathematical mo...

16 Patrick Kidger, et al. ∙

∙ 06/18/2020

When Does Preconditioning Help or Hurt Generalization?

While second order optimizers such as natural gradient descent (NGD) oft...

0 Shun-ichi Amari, et al. ∙

∙ 01/05/2020

Scalable Gradients for Stochastic Differential Equations

The adjoint sensitivity method scalably computes gradients of solutions ...

19 Xuechen Li, et al. ∙

∙ 06/19/2019

Stochastic Runge-Kutta Accelerates Langevin Monte Carlo and Beyond

Sampling with Markov chain Monte Carlo methods typically amounts to disc...

0 Xuechen Li, et al. ∙

∙ 03/25/2019

A Novel Method for the Absolute Pose Problem with Pairwise Constraints

Absolute pose estimation is a fundamental problem in computer vision, an...

0 Yinlong Liu, et al. ∙

∙ 12/29/2018

Fast and Globally Optimal Rigid Registration of 3D Point Sets by Transformation Decomposition

The rigid registration of two 3D point sets is a fundamental problem in ...

0 Xuechen Li, et al. ∙

∙ 04/30/2018

The idemetric property: when most distances are (almost) the same

We introduce the idemetric property, which formalises the idea that most...

0 George Barmpalias, et al. ∙

∙ 02/14/2018

Isolating Sources of Disentanglement in Variational Autoencoders

We decompose the evidence lower bound to show the existence of a term me...

0 Tian Qi Chen, et al. ∙

∙ 01/10/2018

Inference Suboptimality in Variational Autoencoders

Amortized inference has led to efficient approximate inference for large...

0 Chris Cremer, et al. ∙

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