Jian Tang

Affiliations:
  • HEC Montreal, QC, Canada (since 2017)
  • Mila - Quebec AI Institute, Montreal, QC, Canada (since 2017)
  • University of Michigan, Ann Arbor, MI, USA (2016 - 2017)
  • Microsoft Research Asia, Beijing, China (2014 - 2016)
  • Peking University, School of Electronics Engineering and Computer Science, Beijing, China (PhD 2014)


According to our database1, Jian Tang authored at least 134 papers between 2010 and 2024.

Collaborative distances:

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
Other 

Links

Online presence:

On csauthors.net:

Bibliography

2024
Fusing Neural and Physical: Augment Protein Conformation Sampling with Tractable Simulations.
CoRR, 2024

ProtIR: Iterative Refinement between Retrievers and Predictors for Protein Function Annotation.
CoRR, 2024

Structure-Informed Protein Language Model.
CoRR, 2024

Unsupervised Discovery of Steerable Factors When Graph Deep Generative Models Are Entangled.
CoRR, 2024

2023
Multi-modal molecule structure-text model for text-based retrieval and editing.
Nat. Mac. Intell., December, 2023

Full-Scale Information Diffusion Prediction With Reinforced Recurrent Networks.
IEEE Trans. Neural Networks Learn. Syst., May, 2023

Scientific discovery in the age of artificial intelligence.
Nat., 2023

PDB-Struct: A Comprehensive Benchmark for Structure-based Protein Design.
CoRR, 2023

Large Language Models can Learn Rules.
CoRR, 2023

Towards Foundation Models for Knowledge Graph Reasoning.
CoRR, 2023

Towards Foundational Models for Molecular Learning on Large-Scale Multi-Task Datasets.
CoRR, 2023

GraphText: Graph Reasoning in Text Space.
CoRR, 2023

Evolving Computation Graphs.
CoRR, 2023

Score-based Enhanced Sampling for Protein Molecular Dynamics.
CoRR, 2023

GraphVF: Controllable Protein-Specific 3D Molecule Generation with Variational Flow.
CoRR, 2023

Enhancing Protein Language Models with Structure-based Encoder and Pre-training.
CoRR, 2023

A Text-guided Protein Design Framework.
CoRR, 2023

Physics-Inspired Protein Encoder Pre-Training via Siamese Sequence-Structure Diffusion Trajectory Prediction.
CoRR, 2023

A*Net: A Scalable Path-based Reasoning Approach for Knowledge Graphs.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

DiffPack: A Torsional Diffusion Model for Autoregressive Protein Side-Chain Packing.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Pre-Training Protein Encoder via Siamese Sequence-Structure Diffusion Trajectory Prediction.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Symmetry-Informed Geometric Representation for Molecules, Proteins, and Crystalline Materials.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

ProtST: Multi-Modality Learning of Protein Sequences and Biomedical Texts.
Proceedings of the International Conference on Machine Learning, 2023

FusionRetro: Molecule Representation Fusion via In-Context Learning for Retrosynthetic Planning.
Proceedings of the International Conference on Machine Learning, 2023

A Group Symmetric Stochastic Differential Equation Model for Molecule Multi-modal Pretraining.
Proceedings of the International Conference on Machine Learning, 2023

Protein Representation Learning by Geometric Structure Pretraining.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

E3Bind: An End-to-End Equivariant Network for Protein-Ligand Docking.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

Protein Sequence and Structure Co-Design with Equivariant Translation.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

Molecular Geometry Pretraining with SE(3)-Invariant Denoising Distance Matching.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

Learning on Large-scale Text-attributed Graphs via Variational Inference.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

An Empirical Study of Retrieval-Enhanced Graph Neural Networks.
Proceedings of the ECAI 2023 - 26th European Conference on Artificial Intelligence, September 30 - October 4, 2023, Kraków, Poland, 2023

Flaky Performances When Pretraining on Relational Databases (Student Abstract).
Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

Signed Laplacian Graph Neural Networks.
Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022
EurNet: Efficient Multi-Range Relational Modeling of Spatial Multi-Relational Data.
CoRR, 2022

Flaky Performances when Pretraining on Relational Databases.
CoRR, 2022

E3Bind: An End-to-End Equivariant Network for Protein-Ligand Docking.
CoRR, 2022

Metro: Memory-Enhanced Transformer for Retrosynthetic Planning via Reaction Tree.
CoRR, 2022

Evaluating Self-Supervised Learning for Molecular Graph Embeddings.
CoRR, 2022

Learning to Efficiently Propagate for Reasoning on Knowledge Graphs.
CoRR, 2022

Augmenting Message Passing by Retrieving Similar Graphs.
CoRR, 2022

HIRL: A General Framework for Hierarchical Image Representation Learning.
CoRR, 2022

Weakly-supervised Temporal Path Representation Learning with Contrastive Curriculum Learning - Extended Version.
CoRR, 2022

TorchDrug: A Powerful and Flexible Machine Learning Platform for Drug Discovery.
CoRR, 2022

PEER: A Comprehensive and Multi-Task Benchmark for Protein Sequence Understanding.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Inductive Logical Query Answering in Knowledge Graphs.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Neural-Symbolic Models for Logical Queries on Knowledge Graphs.
Proceedings of the International Conference on Machine Learning, 2022

Generative Coarse-Graining of Molecular Conformations.
Proceedings of the International Conference on Machine Learning, 2022

GeoDiff: A Geometric Diffusion Model for Molecular Conformation Generation.
Proceedings of the Tenth International Conference on Learning Representations, 2022

Neural Structured Prediction for Inductive Node Classification.
Proceedings of the Tenth International Conference on Learning Representations, 2022

Pre-training Molecular Graph Representation with 3D Geometry.
Proceedings of the Tenth International Conference on Learning Representations, 2022

Weakly-supervised Temporal Path Representation Learning with Contrastive Curriculum Learning.
Proceedings of the 38th IEEE International Conference on Data Engineering, 2022

Structured Multi-task Learning for Molecular Property Prediction.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

Subgraph Retrieval Enhanced Model for Multi-hop Knowledge Base Question Answering.
Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2022

2021
KEPLER: A Unified Model for Knowledge Embedding and Pre-trained Language Representation.
Trans. Assoc. Comput. Linguistics, 2021

Utilizing graph machine learning within drug discovery and development.
Briefings Bioinform., 2021

Neural Bellman-Ford Networks: A General Graph Neural Network Framework for Link Prediction.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Joint Modeling of Visual Objects and Relations for Scene Graph Generation.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

How to transfer algorithmic reasoning knowledge to learn new algorithms?
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Predicting Molecular Conformation via Dynamic Graph Score Matching.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Neural Algorithmic Reasoners are Implicit Planners.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Artificial Intelligence for Drug Discovery.
Proceedings of the KDD '21: The 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2021

Unsupervised Path Representation Learning with Curriculum Negative Sampling.
Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, 2021

Self-supervised Graph-level Representation Learning with Local and Global Structure.
Proceedings of the 38th International Conference on Machine Learning, 2021

An End-to-End Framework for Molecular Conformation Generation via Bilevel Programming.
Proceedings of the 38th International Conference on Machine Learning, 2021

Learning Gradient Fields for Molecular Conformation Generation.
Proceedings of the 38th International Conference on Machine Learning, 2021

Non-Autoregressive Electron Redistribution Modeling for Reaction Prediction.
Proceedings of the 38th International Conference on Machine Learning, 2021

Learning Neural Generative Dynamics for Molecular Conformation Generation.
Proceedings of the 9th International Conference on Learning Representations, 2021

RNNLogic: Learning Logic Rules for Reasoning on Knowledge Graphs.
Proceedings of the 9th International Conference on Learning Representations, 2021


GraphMix: Improved Training of GNNs for Semi-Supervised Learning.
Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020
Utilising Graph Machine Learning within Drug Discovery and Development.
CoRR, 2020

Sobolev Wasserstein GAN.
CoRR, 2020

COVI-AgentSim: an Agent-based Model for Evaluating Methods of Digital Contact Tracing.
CoRR, 2020

XLVIN: eXecuted Latent Value Iteration Nets.
CoRR, 2020

Graph neural induction of value iteration.
CoRR, 2020

COVI White Paper.
CoRR, 2020

Graph Policy Network for Transferable Active Learning on Graphs.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Continuous Graph Neural Networks.
Proceedings of the 37th International Conference on Machine Learning, 2020

A Graph to Graphs Framework for Retrosynthesis Prediction.
Proceedings of the 37th International Conference on Machine Learning, 2020

Few-shot Relation Extraction via Bayesian Meta-learning on Relation Graphs.
Proceedings of the 37th International Conference on Machine Learning, 2020

Learning to Navigate The Synthetically Accessible Chemical Space Using Reinforcement Learning.
Proceedings of the 37th International Conference on Machine Learning, 2020

InfoGraph: Unsupervised and Semi-supervised Graph-Level Representation Learning via Mutual Information Maximization.
Proceedings of the 8th International Conference on Learning Representations, 2020

GraphAF: a Flow-based Autoregressive Model for Molecular Graph Generation.
Proceedings of the 8th International Conference on Learning Representations, 2020

Deep Geometric Knowledge Distillation with Graphs.
Proceedings of the 2020 IEEE International Conference on Acoustics, 2020

2019
Attending Over Triads for Learning Signed Network Embedding.
Frontiers Big Data, 2019

KEPLER: A Unified Model for Knowledge Embedding and Pre-trained Language Representation.
CoRR, 2019

GraphMix: Regularized Training of Graph Neural Networks for Semi-Supervised Learning.
CoRR, 2019

Data-Driven Approach to Encoding and Decoding 3-D Crystal Structures.
CoRR, 2019

InfoGraph: Unsupervised and Semi-supervised Graph-Level Representation Learning via Mutual Information Maximization.
CoRR, 2019

Weakly-supervised Knowledge Graph Alignment with Adversarial Learning.
CoRR, 2019

Explainable Knowledge Graph-based Recommendation via Deep Reinforcement Learning.
CoRR, 2019

Learning Powerful Policies by Using Consistent Dynamics Model.
CoRR, 2019

Drug-Drug Adverse Effect Prediction with Graph Co-Attention.
CoRR, 2019

GraphVite: A High-Performance CPU-GPU Hybrid System for Node Embedding.
Proceedings of the World Wide Web Conference, 2019

Session-Based Social Recommendation via Dynamic Graph Attention Networks.
Proceedings of the Twelfth ACM International Conference on Web Search and Data Mining, 2019

DivGraphPointer: A Graph Pointer Network for Extracting Diverse Keyphrases.
Proceedings of the 42nd International ACM SIGIR Conference on Research and Development in Information Retrieval, 2019

vGraph: A Generative Model for Joint Community Detection and Node Representation Learning.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Probabilistic Logic Neural Networks for Reasoning.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Multi-scale Information Diffusion Prediction with Reinforced Recurrent Networks.
Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019

GMNN: Graph Markov Neural Networks.
Proceedings of the 36th International Conference on Machine Learning, 2019

RotatE: Knowledge Graph Embedding by Relational Rotation in Complex Space.
Proceedings of the 7th International Conference on Learning Representations, 2019

Structural Robustness for Deep Learning Architectures.
Proceedings of the IEEE Data Science Workshop, 2019

Introducing Graph Smoothness Loss for Training Deep Learning Architectures.
Proceedings of the IEEE Data Science Workshop, 2019

AutoInt: Automatic Feature Interaction Learning via Self-Attentive Neural Networks.
Proceedings of the 28th ACM International Conference on Information and Knowledge Management, 2019

GRLA 2019: The first International Workshop on Graph Representation Learning and its Applications.
Proceedings of the 28th ACM International Conference on Information and Knowledge Management, 2019

Learning Hierarchical Representations of Electronic Health Records for Clinical Outcome Prediction.
Proceedings of the AMIA 2019, 2019

2018
PixelSNE: Pixel-Aligned Stochastic Neighbor Embedding for Efficient 2D Visualization with Screen-Resolution Precision.
Comput. Graph. Forum, 2018

Curriculum Learning for Heterogeneous Star Network Embedding via Deep Reinforcement Learning.
Proceedings of the Eleventh ACM International Conference on Web Search and Data Mining, 2018

DeepInf: Social Influence Prediction with Deep Learning.
Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2018

Learning the Joint Representation of Heterogeneous Temporal Events for Clinical Endpoint Prediction.
Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018

2017
Deriving User Preferences of Mobile Apps from Their Management Activities.
ACM Trans. Inf. Syst., 2017

Roaming across the Castle Tunnels: an Empirical Study of Inter-App Navigation Behaviors of Android Users.
CoRR, 2017

End-to-end Learning for Short Text Expansion.
Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Halifax, NS, Canada, August 13, 2017

An Attention-based Collaboration Framework for Multi-View Network Representation Learning.
Proceedings of the 2017 ACM on Conference on Information and Knowledge Management, 2017

Matching Consumer Health Vocabulary with Professional Medical Terms Through Concept Embedding.
Proceedings of the AMIA 2017, 2017

2016
Less is More: Learning Prominent and Diverse Topics for Data Summarization.
CoRR, 2016

Context-aware Natural Language Generation with Recurrent Neural Networks.
CoRR, 2016

Identity-sensitive Word Embedding through Heterogeneous Networks.
CoRR, 2016

Visualization Large-scale and High-dimensional Data.
CoRR, 2016

PixelSNE: Visualizing Fast with Just Enough Precision via Pixel-Aligned Stochastic Neighbor Embedding.
CoRR, 2016

Visualizing Large-scale and High-dimensional Data.
Proceedings of the 25th International Conference on World Wide Web, 2016

Voting with Their Feet: Inferring User Preferences from App Management Activities.
Proceedings of the 25th International Conference on World Wide Web, 2016

2015
LINE: Large-scale Information Network Embedding.
Proceedings of the 24th International Conference on World Wide Web, 2015

PTE: Predictive Text Embedding through Large-scale Heterogeneous Text Networks.
Proceedings of the 21th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2015

2014
"Look Ma, No Hands!" A Parameter-Free Topic Model.
CoRR, 2014

Understanding the Limiting Factors of Topic Modeling via Posterior Contraction Analysis.
Proceedings of the 31th International Conference on Machine Learning, 2014

Pre-Trained Multi-View Word Embedding Using Two-Side Neural Network.
Proceedings of the Twenty-Eighth AAAI Conference on Artificial Intelligence, 2014

2013
One theme in all views: modeling consensus topics in multiple contexts.
Proceedings of the 19th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2013

2012
Integrating Temporal Usage Pattern into Personalized Tag Prediction.
Proceedings of the Web Technologies and Applications - 14th Asia-Pacific Web Conference, 2012

2011
A trigram hidden Markov model for metadata extraction from heterogeneous references.
Inf. Sci., 2011

Co-Ranking Multiple Entities in a Heterogeneous Network: Integrating Temporal Factor and Users' Bookmarks.
Proceedings of the Digital Libraries: For Cultural Heritage, Knowledge Dissemination, and Future Creation, 2011

Learning to rank audience for behavioral targeting in display ads.
Proceedings of the 20th ACM Conference on Information and Knowledge Management, 2011

Collaborative Users' Brand Preference Mining across Multiple Domains from Implicit Feedbacks.
Proceedings of the Twenty-Fifth AAAI Conference on Artificial Intelligence, 2011

2010
Users' Book-Loan Behaviors Analysis and Knowledge Dependency Mining.
Proceedings of the Web-Age Information Management, 11th International Conference, 2010


  Loading...