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Found 34 papers, 11 papers with code
Contract Structure and Risk Aversion in Longevity Risk Transfers
This paper introduces an economic framework to assess optimal longevity risk transfers between institutions, focusing on the interactions between a buyer exposed to long-term longevity risk and a seller offering longevity protection.
DiffuX2CT: Diffusion Learning to Reconstruct CT Images from Biplanar X-Rays
Computed tomography (CT) is widely utilized in clinical settings because it delivers detailed 3D images of the human body.
Async Learned User Embeddings for Ads Delivery Optimization
In recommendation systems, high-quality user embeddings can capture subtle preferences, enable precise similarity calculations, and adapt to changing preferences over time to maintain relevance.
EditWorld: Simulating World Dynamics for Instruction-Following Image Editing
Therefore, this work, EditWorld, introduces a new editing task, namely world-instructed image editing, which defines and categorizes the instructions grounded by various world scenarios.
Unveiling Nonlinear Dynamics in Catastrophe Bond Pricing: A Machine Learning Perspective
This paper explores the implications of using machine learning models in the pricing of catastrophe (CAT) bonds.
UV-IDM: Identity-Conditioned Latent Diffusion Model for Face UV-Texture Generation
To solve these problems we introduce an Identity-Conditioned Latent Diffusion Model for face UV-texture generation (UV-IDM) to generate photo-realistic textures based on the Basel Face Model (BFM).
IPDreamer: Appearance-Controllable 3D Object Generation with Complex Image Prompts
However, the appearance of 3D objects produced by these text-to-3D models is unpredictable, and it is hard for the single-image-to-3D methods to deal with complex images, thus posing a challenge in generating appearance-controllable 3D objects.
Tree-of-Mixed-Thought: Combining Fast and Slow Thinking for Multi-hop Visual Reasoning
Our approach succeeds in performance while significantly saving inference steps.
Boosting Multi-modal Model Performance with Adaptive Gradient Modulation
In addition, we find that the jointly trained model typically has a preferred modality on which the competition is weaker than other modalities.
Hierarchical Aligned Multimodal Learning for NER on Tweet Posts
Mining structured knowledge from tweets using named entity recognition (NER) can be beneficial for many down stream applications such as recommendation and intention understanding.
Face Animation with an Attribute-Guided Diffusion Model
Face animation has achieved much progress in computer vision.
Improving the Modality Representation with Multi-View Contrastive Learning for Multimodal Sentiment Analysis
At the second stage, a self-supervised contrastive learning is designed for the improvement of the distilled unimodal representations after cross-modal interaction.
Multi-Granularity Cross-Modality Representation Learning for Named Entity Recognition on Social Media
With social media posts tending to be multimodal, Multimodal Named Entity Recognition (MNER) for the text with its accompanying image is attracting more and more attention since some textual components can only be understood in combination with visual information.
CEntRE: A paragraph-level Chinese dataset for Relation Extraction among Enterprises
Enterprise relation extraction aims to detect pairs of enterprise entities and identify the business relations between them from unstructured or semi-structured text data, and it is crucial for several real-world applications such as risk analysis, rating research and supply chain security.
FNeVR: Neural Volume Rendering for Face Animation
In FNeVR, we design a 3D Face Volume Rendering (FVR) module to enhance the facial details for image rendering.
Multi-features based Semantic Augmentation Networks for Named Entity Recognition in Threat Intelligence
Extracting cybersecurity entities such as attackers and vulnerabilities from unstructured network texts is an important part of security analysis.
Rethinking Spatial Invariance of Convolutional Networks for Object Counting
We evaluate our methods on 4 mainstream object counting networks (i. e., MCNN, CSRNet, SANet, and ResNet-50).
Ranked #1 on
Object Counting
on TRANCOS
A Brief Survey on Adaptive Video Streaming Quality Assessment
In this paper, we provide a brief overview of adaptive video streaming quality assessment.
Research on Event Accumulator Settings for Event-Based SLAM
The experiment results show that our method can achieve better performance in most sequences compared with the state-of-the-art event frame based SLAM algorithm.
The Report on China-Spain Joint Clinical Testing for Rapid COVID-19 Risk Screening by Eye-region Manifestations
The image-level performance of COVID-19 prescreening model in the China-Spain multicenter study achieved an AUC of 0. 913 (95% CI, 0. 898-0. 927), with a sensitivity of 0. 695 (95% CI, 0. 643-0. 748), a specificity of 0. 904 (95% CI, 0. 891 -0. 919), an accuracy of 0. 875(0. 861-0. 889), and a F1 of 0. 611(0. 568-0. 655).
A convolutional neural network for teeth margin detection on 3-dimensional dental meshes
The accuracy, recall and precision were validated on 145 dental meshes to rate the best network structures, which were finally tested on another 144 dental meshes.
Rapid COVID-19 Risk Screening by Eye-region Manifestations
It is still nontrivial to develop a new fast COVID-19 screening method with the easier access and lower cost, due to the technical and cost limitations of the current testing methods in the medical resource-poor districts.
Software-Hardware Co-design for Fast and Scalable Training of Deep Learning Recommendation Models
Deep learning recommendation models (DLRMs) are used across many business-critical services at Facebook and are the single largest AI application in terms of infrastructure demand in its data-centers.
Cascade of correlated electron states in a kagome superconductor CsV3Sb5
At a temperature far above the superconducting transition Tc ~ 2. 5 K, we reveal a tri-directional charge order with a 2a0 period that breaks the translation symmetry of the lattice.
Superconductivity Strongly Correlated Electrons
Nanoscale decoupling of electronic nematicity and structural anisotropy in FeSe thin films
In this work, we discover that electronic nematicity can be locally decoupled from the underlying structural anisotropy in strain-engineered iron-selenide (FeSe) thin films.
Strongly Correlated Electrons Materials Science Superconductivity
Finite Volume Element Methods for Two-Dimensional Time Fractional Reaction-Diffusion Equations on Triangular Grids
In this paper, the time fractional reaction-diffusion equations with the Caputo fractional derivative are solved by using the classical $L1$-formula and the finite volume element (FVE) methods on triangular grids.
Numerical Analysis Numerical Analysis 65N30, 65M60, 26A33 G.1.2; G.1.8
Widget Captioning: Generating Natural Language Description for Mobile User Interface Elements
We propose widget captioning, a novel task for automatically generating language descriptions for UI elements from multimodal input including both the image and the structural representations of user interfaces.
A Multi-scale CNN-CRF Framework for Environmental Microorganism Image Segmentation
In order to assist researchers to identify Environmental Microorganisms (EMs) effectively, a Multi-scale CNN-CRF (MSCC) framework for the EM image segmentation is proposed in this paper.
Grassmannian Manifold Optimization Assisted Sparse Spectral Clustering
Spectral Clustering is one of pioneered clustering methods in machine learning and pattern recognition field.
Language Resources and Annotation Tools for Cross-Sentence Relation Extraction
In this paper, we present a novel combination of two types of language resources dedicated to the detection of relevant relations (RE) such as events or facts across sentence boundaries.
Annotating Relation Mentions in Tabloid Press
The current corpus is already in active use in our research for evaluation of the relation extraction performance of our automatically learned extraction patterns.
Multi-label ensemble based on variable pairwise constraint projection
For the boosting-like strategy, we employ both the variable pairwise constraints and the bootstrap steps to diversify the base classifiers.
Annotating Opinions in German Political News
This paper presents an approach to construction of an annotated corpus for German political news for the opinion mining task.
