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08/04/2023
DTF-Net: Category-Level Pose Estimation and Shape Reconstruction via Deformable Template Field
Estimating 6D poses and reconstructing 3D shapes of objects in open-worl...
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06/22/2023
Evolving Computation Graphs
Graph neural networks (GNNs) have demonstrated success in modeling relat...
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06/22/2023
Machine-Learning-Assisted and Real-Time-Feedback-Controlled Growth of InAs/GaAs Quantum Dots
Self-assembled InAs/GaAs quantum dots (QDs) have properties highly valua...
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06/06/2023
RDFC-GAN: RGB-Depth Fusion CycleGAN for Indoor Depth Completion
The raw depth image captured by indoor depth sensors usually has an exte...
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03/23/2023
CMG-Net: An End-to-End Contact-Based Multi-Finger Dexterous Grasping Network
In this paper, we propose a novel representation for grasping using cont...
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03/23/2023
CP^3: Channel Pruning Plug-in for Point-based Networks
Channel pruning can effectively reduce both computational cost and memor...
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03/14/2023
Prioritized Planning for Target-Oriented Manipulation via Hierarchical Stacking Relationship Prediction
In scenarios involving the grasping of multiple targets, the learning of...
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03/11/2023
Enhancing Protein Language Models with Structure-based Encoder and Pre-training
Protein language models (PLMs) pre-trained on large-scale protein sequen...
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01/28/2023
Physics-Inspired Protein Encoder Pre-Training via Siamese Sequence-Structure Diffusion Trajectory Prediction
Pre-training methods on proteins are recently gaining interest, leveragi...
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01/28/2023
ProtST: Multi-Modality Learning of Protein Sequences and Biomedical Texts
Current protein language models (PLMs) learn protein representations mai...
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01/05/2023
Towards Long-Term Time-Series Forecasting: Feature, Pattern, and Distribution
Long-term time-series forecasting (LTTF) has become a pressing demand in...
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12/15/2022
Balanced Datasets for IoT IDS
As the Internet of Things (IoT) continues to grow, cyberattacks are beco...
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11/23/2022
EurNet: Efficient Multi-Range Relational Modeling of Spatial Multi-Relational Data
Modeling spatial relationship in the data remains critical across many d...
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10/26/2022
Learning on Large-scale Text-attributed Graphs via Variational Inference
This paper studies learning on text-attributed graphs (TAGs), where each...
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10/13/2022
Inductive Logical Query Answering in Knowledge Graphs
Formulating and answering logical queries is a standard communication in...
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10/12/2022
E3Bind: An End-to-End Equivariant Network for Protein-Ligand Docking
In silico prediction of the ligand binding pose to a given protein targe...
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09/30/2022
Metro: Memory-Enhanced Transformer for Retrosynthetic Planning via Reaction Tree
Retrosynthetic planning plays a critical role in drug discovery and orga...
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09/28/2022
Debiasing Graph Neural Networks via Learning Disentangled Causal Substructure
Most Graph Neural Networks (GNNs) predict the labels of unseen graphs by...
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07/24/2022
Label-Guided Auxiliary Training Improves 3D Object Detector
Detecting 3D objects from point clouds is a practical yet challenging ta...
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06/07/2022
Learning to Efficiently Propagate for Reasoning on Knowledge Graphs
Path-based methods are more appealing solutions than embedding methods f...
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05/26/2022
HIRL: A General Framework for Hierarchical Image Representation Learning
Learning self-supervised image representations has been broadly studied ...
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05/24/2022
High-Order Pooling for Graph Neural Networks with Tensor Decomposition
Graph Neural Networks (GNNs) are attracting growing attention due to the...
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05/23/2022
Tyger: Task-Type-Generic Active Learning for Molecular Property Prediction
How to accurately predict the properties of molecules is an essential pr...
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05/16/2022
Neural-Symbolic Models for Logical Queries on Knowledge Graphs
Answering complex first-order logic (FOL) queries on knowledge graphs is...
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04/15/2022
Neural Structured Prediction for Inductive Node Classification
This paper studies node classification in the inductive setting, i.e., a...
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03/30/2022
Weakly-supervised Temporal Path Representation Learning with Contrastive Curriculum Learning – Extended Version
In step with the digitalization of transportation, we are witnessing a g...
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03/21/2022
RGB-Depth Fusion GAN for Indoor Depth Completion
The raw depth image captured by the indoor depth sensor usually has an e...
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03/11/2022
Protein Representation Learning by Geometric Structure Pretraining
Learning effective protein representations is critical in a variety of t...
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02/22/2022
Structured Multi-task Learning for Molecular Property Prediction
Multi-task learning for molecular property prediction is becoming increa...
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02/17/2022
CADRE: A Cascade Deep Reinforcement Learning Framework for Vision-based Autonomous Urban Driving
Vision-based autonomous urban driving in dense traffic is quite challeng...
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02/16/2022
TorchDrug: A Powerful and Flexible Machine Learning Platform for Drug Discovery
Machine learning has huge potential to revolutionize the field of drug d...
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02/08/2022
Robotic Grasping from Classical to Modern: A Survey
Robotic Grasping has always been an active topic in robotics since grasp...
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12/18/2021
LegoDNN: Block-grained Scaling of Deep Neural Networks for Mobile Vision
Deep neural networks (DNNs) have become ubiquitous techniques in mobile ...
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12/13/2021
Implications of Topological Imbalance for Representation Learning on Biomedical Knowledge Graphs
Improving on the standard of care for diseases is predicated on better t...
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12/03/2021
Make A Long Image Short: Adaptive Token Length for Vision Transformers
The vision transformer splits each image into a sequence of tokens with ...
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12/01/2021
Training BatchNorm Only in Neural Architecture Search and Beyond
This work investigates the usage of batch normalization in neural archit...
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10/26/2021
How to transfer algorithmic reasoning knowledge to learn new algorithms?
Learning to execute algorithms is a fundamental problem that has been wi...
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10/21/2021
CATRO: Channel Pruning via Class-Aware Trace Ratio Optimization
Deep convolutional neural networks are shown to be overkill with high pa...
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10/11/2021
Neural Algorithmic Reasoners are Implicit Planners
Implicit planning has emerged as an elegant technique for combining lear...
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07/23/2021
Human Pose Transfer with Disentangled Feature Consistency
Deep generative models have made great progress in synthesizing images w...
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06/17/2021
Unsupervised Path Representation Learning with Curriculum Negative Sampling
Path representations are critical in a variety of transportation applica...
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06/13/2021
Neural Bellman-Ford Networks: A General Graph Neural Network Framework for Link Prediction
Link prediction is a very fundamental task on graphs. Inspired by tradit...
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06/08/2021
Non-Autoregressive Electron Redistribution Modeling for Reaction Prediction
Reliably predicting the products of chemical reactions presents a fundam...
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06/08/2021
Self-supervised Graph-level Representation Learning with Local and Global Structure
This paper studies unsupervised/self-supervised whole-graph representati...
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05/15/2021
An End-to-End Framework for Molecular Conformation Generation via Bilevel Programming
Predicting molecular conformations (or 3D structures) from molecular gra...
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05/09/2021
Learning Gradient Fields for Molecular Conformation Generation
We study a fundamental problem in computational chemistry known as molec...
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02/20/2021
Learning Neural Generative Dynamics for Molecular Conformation Generation
We study how to generate molecule conformations (i.e., 3D structures) fr...
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02/19/2021
Lottery Ticket Implies Accuracy Degradation, Is It a Desirable Phenomenon?
In deep model compression, the recent finding "Lottery Ticket Hypothesis...
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12/09/2020
Utilising Graph Machine Learning within Drug Discovery and Development
Graph Machine Learning (GML) is receiving growing interest within the ph...
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12/07/2020