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09/21/2023
A Vision-Centric Approach for Static Map Element Annotation
The recent development of online static map element (a.k.a. HD Map) cons...
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09/12/2023
Normality Learning-based Graph Anomaly Detection via Multi-Scale Contrastive Learning
Graph anomaly detection (GAD) has attracted increasing attention in mach...
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08/31/2023
Can Programming Languages Boost Each Other via Instruction Tuning?
When human programmers have mastered a programming language, it would be...
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08/20/2023
ESTextSpotter: Towards Better Scene Text Spotting with Explicit Synergy in Transformer
In recent years, end-to-end scene text spotting approaches are evolving ...
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07/27/2023
PanGu-Coder2: Boosting Large Language Models for Code with Ranking Feedback
Large Language Models for Code (Code LLM) are flourishing. New and power...
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06/20/2023
RoMe: Towards Large Scale Road Surface Reconstruction via Mesh Representation
Large-scale road surface reconstruction is becoming important to autonom...
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06/09/2023
DocAligner: Annotating Real-world Photographic Document Images by Simply Taking Pictures
Recently, there has been a growing interest in research concerning docum...
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05/15/2023
M^6Doc: A Large-Scale Multi-Format, Multi-Type, Multi-Layout, Multi-Language, Multi-Annotation Category Dataset for Modern Document Layout Analysis
Document layout analysis is a crucial prerequisite for document understa...
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04/11/2023
RecUP-FL: Reconciling Utility and Privacy in Federated Learning via User-configurable Privacy Defense
Federated learning (FL) provides a variety of privacy advantages by allo...
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02/21/2023
Speech Privacy Leakage from Shared Gradients in Distributed Learning
Distributed machine learning paradigms, such as federated learning, have...
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02/01/2023
CoderEval: A Benchmark of Pragmatic Code Generation with Generative Pre-trained Models
Code generation models based on the pre-training and fine-tuning paradig...
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01/17/2023
Recoverability and estimation of causal effects under typical multivariable missingness mechanisms
In the context of missing data, the identifiability or "recoverability" ...
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01/04/2023
SPTS v2: Single-Point Scene Text Spotting
End-to-end scene text spotting has made significant progress due to its ...
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12/08/2022
Towards Accurate Ground Plane Normal Estimation from Ego-Motion
In this paper, we introduce a novel approach for ground plane normal est...
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12/02/2022
Accelerating Inverse Learning via Intelligent Localization with Exploratory Sampling
In the scope of "AI for Science", solving inverse problems is a longstan...
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10/18/2022
ELASTIC: Numerical Reasoning with Adaptive Symbolic Compiler
Numerical reasoning over text is a challenging task of Artificial Intell...
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07/27/2022
Atomic structure generation from reconstructing structural fingerprints
Data-driven machine learning methods have the potential to dramatically ...
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07/23/2022
Marior: Margin Removal and Iterative Content Rectification for Document Dewarping in the Wild
Camera-captured document images usually suffer from perspective and geom...
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03/29/2022
Auditing Privacy Defenses in Federated Learning via Generative Gradient Leakage
Federated Learning (FL) framework brings privacy benefits to distributed...
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12/16/2021
Road-aware Monocular Structure from Motion and Homography Estimation
Structure from motion (SFM) and ground plane homography estimation are c...
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12/15/2021
SPTS: Single-Point Text Spotting
Almost all scene text spotting (detection and recognition) methods rely ...
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12/06/2021
Simulation Intelligence: Towards a New Generation of Scientific Methods
The original "Seven Motifs" set forth a roadmap of essential methods for...
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11/08/2021
On the Stochastic Stability of Deep Markov Models
Deep Markov models (DMM) are generative models that are scalable and exp...
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07/03/2021
Byzantine-robust Federated Learning through Spatial-temporal Analysis of Local Model Updates
Federated Learning (FL) enables multiple distributed clients (e.g., mobi...
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06/06/2021
Inverse design of two-dimensional materials with invertible neural networks
The ability to readily design novel materials with chosen functional pro...
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03/18/2021
Deep Online Correction for Monocular Visual Odometry
In this work, we propose a novel deep online correction (DOC) framework ...
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03/14/2021
A Hybrid Gradient Method to Designing Bayesian Experiments for Implicit Models
Bayesian experimental design (BED) aims at designing an experiment to ma...
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03/14/2021
A Scalable Gradient-Free Method for Bayesian Experimental Design with Implicit Models
Bayesian experimental design (BED) is to answer the question that how to...
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01/24/2021
Towards Robust Visual Information Extraction in Real World: New Dataset and Novel Solution
Visual information extraction (VIE) has attracted considerable attention...
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11/28/2020
Scalable Deep-Learning-Accelerated Topology Optimization for Additively Manufactured Materials
Topology optimization (TO) is a popular and powerful computational appro...
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11/28/2020
Thermodynamic Consistent Neural Networks for Learning Material Interfacial Mechanics
For multilayer materials in thin substrate systems, interfacial failure ...
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11/17/2020
Data Driven Modeling of Interfacial Traction Separation Relations using a Thermodynamically Consistent Neural Network
For multilayer structures, interfacial failure is one of the most import...
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11/02/2020
Modern Monte Carlo Methods for Efficient Uncertainty Quantification and Propagation: A Survey
Uncertainty quantification (UQ) includes the characterization, integrati...
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02/07/2020
A Scalable Evolution Strategy with Directional Gaussian Smoothing for Blackbox Optimization
We developed a new scalable evolution strategy with directional Gaussian...
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08/10/2019
Robust data-driven approach for predicting the configurational energy of high entropy alloys
High entropy alloys (HEAs) have been increasingly attractive as promisin...
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05/31/2018
Uncertainty Quantification and Propagation of Imprecise Probabilities with Copula Dependence Modeling
Imprecise probability allows for partial probability specifications and ...
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03/24/2018
Probability measure changes in Monte Carlo simulation
The objective of Bayesian inference is often to infer, from data, a prob...
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02/26/2018
PBGAN: Partial Binarization of Deconvolution Based Generators
The generator is quite different from the discriminator in a generative ...
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10/09/2017
The effect of prior probabilities on quantification and propagation of imprecise probabilities resulting from small datasets
This paper outlines a methodology for Bayesian multimodel uncertainty qu...
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10/29/2014
