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09/19/2023
Graph Contrastive Learning Meets Graph Meta Learning: A Unified Method for Few-shot Node Tasks
Graph Neural Networks (GNNs) have become popular in Graph Representation...
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08/31/2023
CktGNN: Circuit Graph Neural Network for Electronic Design Automation
The electronic design automation of analog circuits has been a longstand...
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08/08/2023
3D-VisTA: Pre-trained Transformer for 3D Vision and Text Alignment
3D vision-language grounding (3D-VL) is an emerging field that aims to c...
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07/26/2023
PNT-Edge: Towards Robust Edge Detection with Noisy Labels by Learning Pixel-level Noise Transitions
Relying on large-scale training data with pixel-level labels, previous e...
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07/24/2023
SL: Stable Learning in Source-Free Domain Adaption for Medical Image Segmentation
Deep learning techniques for medical image analysis usually suffer from ...
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06/05/2023
Towards Arbitrarily Expressive GNNs in O(n^2) Space by Rethinking Folklore Weisfeiler-Lehman
Message passing neural networks (MPNNs) have emerged as the most popular...
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05/23/2023
Improving Heterogeneous Model Reuse by Density Estimation
This paper studies multiparty learning, aiming to learn a model using th...
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04/26/2023
FVP: Fourier Visual Prompting for Source-Free Unsupervised Domain Adaptation of Medical Image Segmentation
Medical image segmentation methods normally perform poorly when there is...
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04/20/2023
Recurrent Transformer for Dynamic Graph Representation Learning with Edge Temporal States
Dynamic graph representation learning is growing as a trending yet chall...
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03/21/2023
Learning Context-aware Classifier for Semantic Segmentation
Semantic segmentation is still a challenging task for parsing diverse co...
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03/06/2023
Detecting Human-Object Contact in Images
Humans constantly contact objects to move and perform tasks. Thus, detec...
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03/05/2023
Time Associated Meta Learning for Clinical Prediction
Rich Electronic Health Records (EHR), have created opportunities to impr...
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01/27/2023
A Multi-View Joint Learning Framework for Embedding Clinical Codes and Text Using Graph Neural Networks
Learning to represent free text is a core task in many clinical machine ...
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12/29/2022
On Transforming Reinforcement Learning by Transformer: The Development Trajectory
Transformer, originally devised for natural language processing, has als...
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12/04/2022
Toward Efficient Language Model Pretraining and Downstream Adaptation via Self-Evolution: A Case Study on SuperGLUE
This technical report briefly describes our JDExplore d-team's Vega v2 s...
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11/08/2022
Algorithmic Bias in Machine Learning Based Delirium Prediction
Although prediction models for delirium, a commonly occurring condition ...
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10/18/2022
HUMANISE: Language-conditioned Human Motion Generation in 3D Scenes
Learning to generate diverse scene-aware and goal-oriented human motions...
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10/06/2022
Geodesic Graph Neural Network for Efficient Graph Representation Learning
Recently, Graph Neural Networks (GNNs) have been applied to graph learni...
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09/19/2022
Interpreting mechanism of Synergism of drug combinations using attention based hierarchical graph pooling
The synergistic drug combinations provide huge potentials to enhance the...
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06/22/2022
Deep Learning to Jointly Schema Match, Impute, and Transform Databases
An applied problem facing all areas of data science is harmonizing data ...
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06/20/2022
DASH: Distributed Adaptive Sequencing Heuristic for Submodular Maximization
The development of parallelizable algorithms for monotone, submodular ma...
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05/26/2022
How Powerful are K-hop Message Passing Graph Neural Networks
The most popular design paradigm for Graph Neural Networks (GNNs) is 1-h...
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04/20/2022
One-Class Model for Fabric Defect Detection
An automated and accurate fabric defect inspection system is in high dem...
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04/14/2022
Learning Convolutional Neural Networks in the Frequency Domain
Convolutional neural network (CNN) has achieved impressive success in co...
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04/01/2022
Multi-Agent Path Planning with Asymmetric Interactions In Tight Spaces
By starting with the assumption that motion is fundamentally a decision ...
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03/19/2022
PACE: A Parallelizable Computation Encoder for Directed Acyclic Graphs
Optimization of directed acyclic graph (DAG) structures has many applica...
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03/02/2022
SEA: Bridging the Gap Between One- and Two-stage Detector Distillation via SEmantic-aware Alignment
We revisit the one- and two-stage detector distillation tasks and presen...
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11/15/2021
Best of Both Worlds: Practical and Theoretically Optimal Submodular Maximization in Parallel
For the problem of maximizing a monotone, submodular function with respe...
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10/14/2021
Training Neural Networks for Solving 1-D Optimal Piecewise Linear Approximation
Recently, the interpretability of deep learning has attracted a lot of a...
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09/27/2021
Deep Structured Instance Graph for Distilling Object Detectors
Effectively structuring deep knowledge plays a pivotal role in transfer ...
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09/08/2021
YouRefIt: Embodied Reference Understanding with Language and Gesture
We study the understanding of embodied reference: One agent uses both la...
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09/07/2021
CIM: Class-Irrelevant Mapping for Few-Shot Classification
Few-shot classification (FSC) is one of the most concerned hot issues in...
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08/30/2021
Exploring and Improving Mobile Level Vision Transformers
We study the vision transformer structure in the mobile level in this pa...
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07/19/2021
A Modulation Layer to Increase Neural Network Robustness Against Data Quality Issues
Data quality is a common problem in machine learning, especially in high...
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05/17/2021
Fast and Accurate Quantized Camera Scene Detection on Smartphones, Mobile AI 2021 Challenge: Report
Camera scene detection is among the most popular computer vision problem...
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05/17/2021
Real-Time Quantized Image Super-Resolution on Mobile NPUs, Mobile AI 2021 Challenge: Report
Image super-resolution is one of the most popular computer vision proble...
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05/14/2021
Interpretable Drug Synergy Prediction with Graph Neural Networks for Human-AI Collaboration in Healthcare
We investigate molecular mechanisms of resistant or sensitive response o...
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01/28/2021
GPU Optimization for High-Quality Kinetic Fluid Simulation
Fluid simulations are often performed using the incompressible Navier-St...
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01/16/2021
Non-convex weakly smooth Langevin Monte Carlo using regularization
Discretization of continuous-time diffusion processes is a widely recogn...
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11/03/2020
(Un)fairness in Post-operative Complication Prediction Models
With the current ongoing debate about fairness, explainability and trans...
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07/31/2020
LEMMA: A Multi-view Dataset for Learning Multi-agent Multi-task Activities
Understanding and interpreting human actions is a long-standing challeng...
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06/11/2020
Closed Loop Neural-Symbolic Learning via Integrating Neural Perception, Grammar Parsing, and Symbolic Reasoning
The goal of neural-symbolic computation is to integrate the connectionis...
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03/17/2020
DEPARA: Deep Attribution Graph for Deep Knowledge Transferability
Exploring the intrinsic interconnections between the knowledge encoded i...
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12/16/2019
PerspectiveNet: 3D Object Detection from a Single RGB Image via Perspective Points
Detecting 3D objects from a single RGB image is intrinsically ambiguous,...
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09/26/2019
Deep Model Transferability from Attribution Maps
Exploring the transferability between heterogeneous tasks sheds light on...
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09/04/2019
Holistic++ Scene Understanding: Single-view 3D Holistic Scene Parsing and Human Pose Estimation with Human-Object Interaction and Physical Commonsense
We propose a new 3D holistic++ scene understanding problem, which jointl...
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07/29/2019
A Factored Generalized Additive Model for Clinical Decision Support in the Operating Room
Logistic regression (LR) is widely used in clinical prediction because i...
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07/25/2019
Graph Neural Lasso for Dynamic Network Regression
In this paper, we will study the dynamic network regression problem, whi...
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06/05/2019
Estimating Feature-Label Dependence Using Gini Distance Statistics
Identifying statistical dependence between the features and the label is...
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04/26/2019