Jian Tang
98 papers · 2014–2025 · 14 conferences · across top CS/AI conferences
Achievements
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πΊοΈ Taxonomy Completionist (22) π§ Keyword Pioneer π Interdisciplinary Bridge π Renaissance Researcher (5) π£ Hot Topic Early Bird
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Renaissance Researcher
(5)
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Interdisciplinary Bridge
πΊοΈ
Taxonomy Completionist
(22)
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Conference Loyalist
(27)
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Deep Specialist
(19)
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Triple Crown
π§¬
Topic Evolution
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Keyword Champion
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Grand Slam
π₯
Mega-Team
(37)
π€
Dynamic Duo
(14)
β
The Questioner
(2)
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Conference Pioneer
β‘
Prolific Year
(13)
π₯
Unstoppable
(10)
ποΈ
Keyword Collector
(68)
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Century Club
(98)
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Trend Setter
Conferences
NIPS (27)
ICLR (21)
ICML (18)
AAAI (11)
CVPR (5)
ECCV (4)
INTERSPEECH (3)
ICCV (2)
IJCAI (2)
ACL (1)
AISTATS (1)
EMNLP (1)
NAACL (1)
RSS (1)
Top co-authors
Research topics
Keywords
graph neural network
(20)
model compression
(7)
knowledge graph
(6)
self-supervised learning
(5)
representation learning
(5)
variational inference
(5)
node classification
(5)
multi-modal learning
(5)
reinforcement learning
(4)
knowledge distillation
(4)
transfer learning
(4)
molecular graph
(4)
zero-shot learning
(3)
protein structure
(3)
protein language model
(3)
multi-task learning
(3)
neural network pruning
(3)
link prediction
(3)
neural network optimization
(3)
graph representation learning
(2)
Papers
RoboMIND: Benchmark on Multi-embodiment Intelligence Normative Data for Robot Manipulation
RSS 2025
GlycanML: A Multi-Task and Multi-Structure Benchmark for Glycan Machine Learning
ICLR 2025
Training-free Generation of Temporally Consistent Rewards from VLMs
ICCV 2025
Structure Language Models for Protein Conformation Generation
ICLR 2025
Fully-inductive Node Classification on Arbitrary Graphs
ICLR 2025
Aligning Protein Conformation Ensemble Generation with Physical Feedback
ICML 2025
Exploring Gradient Explosion in Generative Adversarial Imitation Learning: A Probabilistic Perspective
AAAI 2024
Str2Str: A Score-based Framework for Zero-shot Protein Conformation Sampling
ICLR 2024
Retrieval-Augmented Embodied Agents
CVPR 2024
AI for Science in the Era of Large Language Models
EMNLP 2024
Towards Foundation Models for Knowledge Graph Reasoning
ICLR 2024
Cell ontology guided transcriptome foundation model
NIPS 2024
A Foundation Model for Zero-shot Logical Query Reasoning
NIPS 2024
Multi-Scale Representation Learning for Protein Fitness Prediction
NIPS 2024
Any2Policy: Learning Visuomotor Policy with Any-Modality
NIPS 2024
EDT: An Efficient Diffusion Transformer Framework Inspired by Human-like Sketching
NIPS 2024
Evaluating Representation Learning on the Protein Structure Universe
ICLR 2024
Towards Foundational Models for Molecular Learning on Large-Scale Multi-Task Datasets
ICLR 2024
EPSD: Early Pruning with Self-Distillation for Efficient Model Compression
AAAI 2024
Symmetry-Informed Geometric Representation for Molecules, Proteins, and Crystalline Materials
NIPS 2023
Evaluating Self-Supervised Learning for Molecular Graph Embeddings
NIPS 2023
GAUCHE: A Library for Gaussian Processes in Chemistry
NIPS 2023
Learning on Large-scale Text-attributed Graphs via Variational Inference
ICLR 2023
Molecular Geometry Pretraining with SE(3)-Invariant Denoising Distance Matching
ICLR 2023
Protein Representation Learning by Geometric Structure Pretraining
ICLR 2023
E3Bind: An End-to-End Equivariant Network for Protein-Ligand Docking
ICLR 2023
Protein Sequence and Structure Co-Design with Equivariant Translation
ICLR 2023
Signed Laplacian Graph Neural Networks
AAAI 2023
Flaky Performances When Pretraining on Relational Databases (Student Abstract)
AAAI 2023
CP3: Channel Pruning Plug-In for Point-Based Networks
CVPR 2023
ScaleKD: Distilling Scale-Aware Knowledge in Small Object Detector
CVPR 2023
ProtST: Multi-Modality Learning of Protein Sequences and Biomedical Texts
ICML 2023
FusionRetro: Molecule Representation Fusion via In-Context Learning for Retrosynthetic Planning
ICML 2023
A Group Symmetric Stochastic Differential Equation Model for Molecule Multi-modal Pretraining
ICML 2023
Pre-Training Protein Encoder via Siamese Sequence-Structure Diffusion Trajectory Prediction
NIPS 2023
DiffPack: A Torsional Diffusion Model for Autoregressive Protein Side-Chain Packing
NIPS 2023
A*Net: A Scalable Path-based Reasoning Approach for Knowledge Graphs
NIPS 2023
Generative Coarse-Graining of Molecular Conformations
ICML 2022
High-Order Pooling for Graph Neural Networks with Tensor Decomposition
NIPS 2022
Inductive Logical Query Answering in Knowledge Graphs
NIPS 2022
Debiasing Graph Neural Networks via Learning Disentangled Causal Substructure
NIPS 2022
Teach Less, Learn More: On the Undistillable Classes in Knowledge Distillation
NIPS 2022
PEER: A Comprehensive and Multi-Task Benchmark for Protein Sequence Understanding
NIPS 2022
CADRE: A Cascade Deep Reinforcement Learning Framework for Vision-Based Autonomous Urban Driving
AAAI 2022
Subgraph Retrieval Enhanced Model for Multi-hop Knowledge Base Question Answering
ACL 2022
Structured Multi-task Learning for Molecular Property Prediction
AISTATS 2022
RGB-Depth Fusion GAN for Indoor Depth Completion
CVPR 2022
Label-Guided Auxiliary Training Improves 3D Object Detector
ECCV 2022
Pre-training Molecular Graph Representation with 3D Geometry
ICLR 2022
Neural Structured Prediction for Inductive Node Classification
ICLR 2022
GeoDiff: A Geometric Diffusion Model for Molecular Conformation Generation
ICLR 2022
Neural-Symbolic Models for Logical Queries on Knowledge Graphs
ICML 2022
GraphMix: Improved Training of GNNs for Semi-Supervised Learning
AAAI 2021
RNNLogic: Learning Logic Rules for Reasoning on Knowledge Graphs
ICLR 2021
Learning Neural Generative Dynamics for Molecular Conformation Generation
ICLR 2021
Predicting Infectiousness for Proactive Contact Tracing
ICLR 2021
Feature-level Incongruence Reduction for Multimodal Translation
NAACL 2021
Neural Bellman-Ford Networks: A General Graph Neural Network Framework for Link Prediction
NIPS 2021
Predicting Molecular Conformation via Dynamic Graph Score Matching
NIPS 2021
How to transfer algorithmic reasoning knowledge to learn new algorithms?
NIPS 2021
Neural Algorithmic Reasoners are Implicit Planners
NIPS 2021
Joint Modeling of Visual Objects and Relations for Scene Graph Generation
NIPS 2021
Non-Autoregressive Electron Redistribution Modeling for Reaction Prediction
ICML 2021
Lottery Ticket Preserves Weight Correlation: Is It Desirable or Not?
ICML 2021
Learning Gradient Fields for Molecular Conformation Generation
ICML 2021
An End-to-End Framework for Molecular Conformation Generation via Bilevel Programming
ICML 2021
Self-supervised Graph-level Representation Learning with Local and Global Structure
ICML 2021
Unsupervised Path Representation Learning with Curriculum Negative Sampling
IJCAI 2021
Hierarchical Graph Attention Network for Few-Shot Visual-Semantic Learning
ICCV 2021
Knowledge Transfer in Multi-Task Deep Reinforcement Learning for Continuous Control
NIPS 2020
Graph Policy Network for Transferable Active Learning on Graphs
NIPS 2020
Towards Interpretable Natural Language Understanding with Explanations as Latent Variables
NIPS 2020
Learning Dynamic Belief Graphs to Generalize on Text-Based Games
NIPS 2020
Learning to Navigate The Synthetically Accessible Chemical Space Using Reinforcement Learning
ICML 2020
Few-shot Relation Extraction via Bayesian Meta-learning on Relation Graphs
ICML 2020
A Graph to Graphs Framework for Retrosynthesis Prediction
ICML 2020
Continuous Graph Neural Networks
ICML 2020
GraphAF: a Flow-based Autoregressive Model for Molecular Graph Generation
ICLR 2020
InfoGraph: Unsupervised and Semi-supervised Graph-Level Representation Learning via Mutual Information Maximization
ICLR 2020
Differentiable Feature Aggregation Search for Knowledge Distillation
ECCV 2020
An Image Enhancing Pattern-based Sparsity for Real-time Inference on Mobile Devices
ECCV 2020
Domain Conditioned Adaptation Network
AAAI 2020
PCONV: The Missing but Desirable Sparsity in DNN Weight Pruning for Real-Time Execution on Mobile Devices
AAAI 2020
AutoCompress: An Automatic DNN Structured Pruning Framework for Ultra-High Compression Rates
AAAI 2020
Universal Approximation Property and Equivalence of Stochastic Computing-Based Neural Networks and Binary Neural Networks
AAAI 2019
GMNN: Graph Markov Neural Networks
ICML 2019
Probabilistic Logic Neural Networks for Reasoning
NIPS 2019
Signal-To-Noise Ratio: A Robust Distance Metric for Deep Metric Learning
CVPR 2019
Multi-scale Information Diffusion Prediction with Reinforced Recurrent Networks
IJCAI 2019
RotatE: Knowledge Graph Embedding by Relational Rotation in Complex Space
ICLR 2019
Contextualized Non-Local Neural Networks for Sequence Learning
AAAI 2019
vGraph: A Generative Model for Joint Community Detection and Node Representation Learning
NIPS 2019
Acoustic Modeling with Densely Connected Residual Network for Multichannel Speech Recognition
INTERSPEECH 2018
A Systematic DNN Weight Pruning Framework using Alternating Direction Method of Multipliers
ECCV 2018
Theoretical Properties for Neural Networks with Weight Matrices of Low Displacement Rank
ICML 2017
RNN-BLSTM Based Multi-Pitch Estimation
INTERSPEECH 2016
Future Context Attention for Unidirectional LSTM Based Acoustic Model
INTERSPEECH 2016
Understanding the Limiting Factors of Topic Modeling via Posterior Contraction Analysis
ICML 2014