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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...
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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...
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05/17/2023
Two-Stream Regression Network for Dental Implant Position Prediction
In implant prosthesis treatment, the design of surgical guide requires l...
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03/28/2023
Foundation Models and Fair Use
Existing foundation models are trained on copyrighted material. Deployin...
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02/11/2023
Exploiting Programmatic Behavior of LLMs: Dual-Use Through Standard Security Attacks
Recent advances in instruction-following large language models (LLMs) ha...
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11/16/2022
Holistic Evaluation of Language Models
Language models (LMs) are becoming the foundation for almost all major l...
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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 ...
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10/25/2022
Synthetic Text Generation with Differential Privacy: A Simple and Practical Recipe
Privacy concerns have attracted increasing attention in data-driven prod...
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10/15/2022
A Closer Look at the Calibration of Differentially Private Learners
We systematically study the calibration of classifiers trained with diff...
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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...
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07/01/2022
When Does Differentially Private Learning Not Suffer in High Dimensions?
Large pretrained models can be privately fine-tuned to achieve performan...
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10/12/2021
Large Language Models Can Be Strong Differentially Private Learners
Differentially Private (DP) learning has seen limited success for buildi...
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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 ...
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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...
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05/27/2021
Efficient and Accurate Gradients for Neural SDEs
Neural SDEs combine many of the best qualities of both RNNs and SDEs, an...
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02/12/2021
Infinitely Deep Bayesian Neural Networks with Stochastic Differential Equations
We perform scalable approximate inference in a recently-proposed family ...
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02/06/2021
Neural SDEs as Infinite-Dimensional GANs
Stochastic differential equations (SDEs) are a staple of mathematical mo...
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06/18/2020
When Does Preconditioning Help or Hurt Generalization?
While second order optimizers such as natural gradient descent (NGD) oft...
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01/05/2020
Scalable Gradients for Stochastic Differential Equations
The adjoint sensitivity method scalably computes gradients of solutions ...
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06/19/2019
Stochastic Runge-Kutta Accelerates Langevin Monte Carlo and Beyond
Sampling with Markov chain Monte Carlo methods typically amounts to disc...
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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...
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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 ...
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04/30/2018
The idemetric property: when most distances are (almost) the same
We introduce the idemetric property, which formalises the idea that most...
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02/14/2018
Isolating Sources of Disentanglement in Variational Autoencoders
We decompose the evidence lower bound to show the existence of a term me...
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01/10/2018