
Learning Neural Generative Dynamics for Molecular Conformation Generation
We study how to generate molecule conformations (i.e., 3D structures) fr...
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Lottery Ticket Implies Accuracy Degradation, Is It a Desirable Phenomenon?
In deep model compression, the recent finding "Lottery Ticket Hypothesis...
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Utilising Graph Machine Learning within Drug Discovery and Development
Graph Machine Learning (GML) is receiving growing interest within the ph...
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Sobolev Wasserstein GAN
Wasserstein GANs (WGANs), built upon the KantorovichRubinstein (KR) dua...
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Fast Object Detection with Latticed MultiScale Feature Fusion
Scale variance is one of the crucial challenges in multiscale object de...
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Robust Unsupervised Video Anomaly Detection by MultiPath Frame Prediction
Video anomaly detection is commonly used in many applications such as se...
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DAIS: Automatic Channel Pruning via Differentiable Annealing Indicator Search
The convolutional neural network has achieved great success in fulfillin...
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P^2 Net: Augmented ParallelPyramid Net for Attention Guided Pose Estimation
We propose an augmented ParallelPyramid Net (P^2 Net) with feature refi...
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XLVIN: eXecuted Latent Value Iteration Nets
Value Iteration Networks (VINs) have emerged as a popular method to inco...
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Iterative Graph SelfDistillation
How to discriminatively vectorize graphs is a fundamental challenge that...
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Knowledge Transfer in MultiTask Deep Reinforcement Learning for Continuous Control
While Deep Reinforcement Learning (DRL) has emerged as a promising appro...
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RNNLogic: Learning Logic Rules for Reasoning on Knowledge Graphs
This paper studies learning logic rules for reasoning on knowledge graph...
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Graph neural induction of value iteration
Many reinforcement learning tasks can benefit from explicit planning bas...
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Differentiable Feature Aggregation Search for Knowledge Distillation
Knowledge distillation has become increasingly important in model compre...
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GRADE: Graph Dynamic Embedding
Representation learning of static and more recently dynamically evolving...
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Fewshot Relation Extraction via Bayesian Metalearning on Relation Graphs
This paper studies fewshot relation extraction, which aims at predictin...
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An Advert Creation System for 3D Product Placements
Over the past decade, the evolution of videosharing platforms has attra...
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Graph Policy Network for Transferable Active Learning on Graphs
Graph neural networks (GNNs) have been attracting increasing popularity ...
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Domain Conditioned Adaptation Network
Tremendous research efforts have been made to thrive deep domain adaptat...
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Investigating Classlevel Difficulty Factors in Multilabel Classification Problems
This work investigates the use of classlevel difficulty factors in mult...
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Learning To Navigate The Synthetically Accessible Chemical Space Using Reinforcement Learning
Over the last decade, there has been significant progress in the field o...
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A Graph to Graphs Framework for Retrosynthesis Prediction
A fundamental problem in computational chemistry is to find a set of rea...
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Learning Dynamic Knowledge Graphs to Generalize on TextBased Games
Playing textbased games requires skill in processing natural language a...
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GraphAF: a Flowbased Autoregressive Model for Molecular Graph Generation
Molecular graph generation is a fundamental problem for drug discovery a...
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BLKREW: A Unified Blockbased DNN Pruning Framework using Reweighted Regularization Method
Accelerating DNN execution on various resourcelimited computing platfor...
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An Image Enhancing Patternbased Sparsity for Realtime Inference on Mobile Devices
Weight pruning has been widely acknowledged as a straightforward and eff...
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Continuous Graph Neural Networks
This paper builds the connection between graph neural networks and tradi...
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KEPLER: A Unified Model for Knowledge Embedding and Pretrained Language Representation
Pretrained language representation models (PLMs) learn effective langua...
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Deep geometric knowledge distillation with graphs
In most cases deep learning architectures are trained disregarding the a...
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Identifying Candidate Spaces for Advert Implantation
Virtual advertising is an important and promising feature in the area of...
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GraphMix: Regularized Training of Graph Neural Networks for SemiSupervised Learning
We present GraphMix, a regularization technique for Graph Neural Network...
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Structural Robustness for Deep Learning Architectures
Deep Networks have been shown to provide stateoftheart performance in...
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PCONV: The Missing but Desirable Sparsity in DNN Weight Pruning for Realtime Execution on Mobile Devices
Model compression techniques on Deep Neural Network (DNN) have been wide...
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DataDriven Approach to Encoding and Decoding 3D Crystal Structures
Generative models have achieved impressive results in many domains inclu...
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An EndtoEnd Neighborhoodbased Interaction Model for Knowledgeenhanced Recommendation
This paper studies graphbased recommendation, where an interaction grap...
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InfoGraph: Unsupervised and Semisupervised GraphLevel Representation Learning via Mutual Information Maximization
This paper studies learning the representations of whole graphs in both ...
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Weaklysupervised Knowledge Graph Alignment with Adversarial Learning
This paper studies aligning knowledge graphs from different sources or l...
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AutoSlim: An Automatic DNN Structured Pruning Framework for UltraHigh Compression Rates
Structured weight pruning is a representative model compression techniqu...
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AutoCompress: An Automatic DNN Structured Pruning Framework for UltraHigh Compression Rates
Structured weight pruning is a representative model compression techniqu...
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Explainable Knowledge Graphbased Recommendation via Deep Reinforcement Learning
This paper studies recommender systems with knowledge graphs, which can ...
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Probabilistic Logic Neural Networks for Reasoning
Knowledge graph reasoning, which aims at predicting the missing facts th...
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vGraph: A Generative Model for Joint Community Detection and Node Representation Learning
This paper focuses on two fundamental tasks of graph analysis: community...
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Learning Powerful Policies by Using Consistent Dynamics Model
Modelbased Reinforcement Learning approaches have the promise of being ...
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DivGraphPointer: A Graph Pointer Network for Extracting Diverse Keyphrases
Keyphrase extraction from documents is useful to a variety of applicatio...
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GMNN: Graph Markov Neural Networks
This paper studies semisupervised object classification in relational d...
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Localizing Adverts in Outdoor Scenes
Online videos have witnessed an unprecedented growth over the last decad...
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DrugDrug Adverse Effect Prediction with Graph CoAttention
Complex or coexisting diseases are commonly treated using drug combinat...
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Introducing Graph Smoothness Loss for Training Deep Learning Architectures
We introduce a novel loss function for training deep learning architectu...
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Softmax Optimizations for Intel Xeon Processorbased Platforms
Softmax is popular normalization method used in machine learning. Deep l...
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The ALOS Dataset for Advert Localization in Outdoor Scenes
The rapid increase in the number of online videos provides the marketing...
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Jian Tang
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Assistant Professor at HEC Montréal & Montreal Institute for Learning Algorithms since 2017, Associate Researcher at Microsoft Research Asia from 20142016, Visiting Student at University of Michigan from 20112013, Intern at Microsoft Research Asia from 20102011