Jure Leskovec
107 papers · 2010–2025 · 13 venues · across top CS/AI venues
Authors are matched by name, so researchers who share a name ("Yang Liu", "Wei Wang") appear as a single profile and their paper counts, venues and achievements are combined. How identity is handled.
Achievements
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Research topics
Machine Learning
(73)
Deep Learning
(50)
Artificial Intelligence
(41)
Architectures
(41)
Core Methods
(40)
Core AI
(32)
Learning Types Β· Machine Learning
(25)
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(18)
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(11)
Mathematics & Optimization
(11)
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(10)
Learning Types Β· Deep Learning
(10)
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(9)
Techniques
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Keywords
graph neural network
(35)
link prediction
(14)
knowledge graph
(11)
representation learning
(10)
node classification
(7)
message passing
(5)
graph representation learning
(4)
few-shot learning
(4)
question answering
(4)
generative model
(4)
language model
(4)
dynamic network
(4)
attention mechanism
(3)
diffusion model
(3)
in-context learning
(3)
knowledge graph embedding
(3)
node embedding
(3)
distribution shift
(3)
network inference
(3)
graph generation
(3)
Papers
Automated Hypothesis Validation with Agentic Sequential Falsifications
ICML 2025
BioDiscoveryAgent: An AI Agent for Designing Genetic Perturbation Experiments
ICLR 2025
CollabLLM: From Passive Responders to Active Collaborators
ICML 2025
ContextGNN: Beyond Two-Tower Recommendation Systems
ICLR 2025
Energy-Based Diffusion Language Models for Text Generation
ICLR 2025
Holographic Node Representations: Pre-training Task-Agnostic Node Embeddings
ICLR 2025
Large Language Models are Good Relational Learners
ACL 2025
Learning Efficient Positional Encodings with Graph Neural Networks
ICLR 2025
Learning Production Functions for Supply Chains with Graph Neural Networks
AAAI 2025
RelGNN: Composite Message Passing for Relational Deep Learning
ICML 2025
TabDiff: a Mixed-type Diffusion Model for Tabular Data Generation
ICLR 2025
Zero-Shot Generalization of GNNs over Distinct Attribute Domains
ICML 2025
Aligning Target-Aware Molecule Diffusion Models with Exact Energy Optimization
NeurIPS 2024
AvaTaR: Optimizing LLM Agents for Tool Usage via Contrastive Reasoning
NeurIPS 2024
Compositional Generative Inverse Design
ICLR 2024
Context-Aware Meta-Learning
ICLR 2024
Equivariant Graph Neural Operator for Modeling 3D Dynamics
ICML 2024
From Similarity to Superiority: Channel Clustering for Time Series Forecasting
NeurIPS 2024
GraphMETRO: Mitigating Complex Graph Distribution Shifts via Mixture of Aligned Experts
NeurIPS 2024
Inferring Dynamic Networks from Marginals with Iterative Proportional Fitting
ICML 2024
Large Language Models as Analogical Reasoners
ICLR 2024
MLAgentBench: Evaluating Language Agents on Machine Learning Experimentation
ICML 2024
Position: Relational Deep Learning - Graph Representation Learning on Relational Databases
ICML 2024
RelBench: A Benchmark for Deep Learning on Relational Databases
NeurIPS 2024
STaRK: Benchmarking LLM Retrieval on Textual and Relational Knowledge Bases
NeurIPS 2024
Uncertainty Quantification for Forward and Inverse Problems of PDEs via Latent Global Evolution
AAAI 2024
VQGraph: Rethinking Graph Representation Space for Bridging GNNs and MLPs
ICLR 2024
AutoTransfer: AutoML with Knowledge Transfer - An Application to Graph Neural Networks
ICLR 2023
Estimating Geographic Spillover Effects of COVID-19 Policies from Large-Scale Mobility Networks
AAAI 2023
Geometric Latent Diffusion Models for 3D Molecule Generation
ICML 2023
High dimensional, tabular deep learning with an auxiliary knowledge graph
NeurIPS 2023
Holistic Evaluation of Text-to-Image Models
NeurIPS 2023
Learning Controllable Adaptive Simulation for Multi-resolution Physics
ICLR 2023
Learning Large Graph Property Prediction via Graph Segment Training
NeurIPS 2023
PRODIGY: Enabling In-context Learning Over Graphs
NeurIPS 2023
Retrieval-Augmented Multimodal Language Modeling
ICML 2023
Temporal Graph Benchmark for Machine Learning on Temporal Graphs
NeurIPS 2023
Uncertainty Quantification over Graph with Conformalized Graph Neural Networks
NeurIPS 2023
VQA-GNN: Reasoning with Multimodal Knowledge via Graph Neural Networks for Visual Question Answering
ICCV 2023
When Do Graph Neural Networks Help with Node Classification? Investigating the Homophily Principle on Node Distinguishability
NeurIPS 2023
Zero-shot causal learning
NeurIPS 2023
Data-Driven Real-Time Strategic Placement of Mobile Vaccine Distribution Sites
AAAI 2022
Deep Bidirectional Language-Knowledge Graph Pretraining
NeurIPS 2022
Extending the WILDS Benchmark for Unsupervised Adaptation
ICLR 2022
Few-shot Relational Reasoning via Connection Subgraph Pretraining
NeurIPS 2022
GreaseLM: Graph REASoning Enhanced Language Models
ICLR 2022
Learning to Accelerate Partial Differential Equations via Latent Global Evolution
NeurIPS 2022
LinkBERT: Pretraining Language Models with Document Links
ACL 2022
Open-World Semi-Supervised Learning
ICLR 2022
Relational Multi-Task Learning: Modeling Relations between Data and Tasks
ICLR 2022
ZeroC: A Neuro-Symbolic Model for Zero-shot Concept Recognition and Acquisition at Inference Time
NeurIPS 2022
Combiner: Full Attention Transformer with Sparse Computation Cost
NeurIPS 2021
Concept Learners for Few-Shot Learning
ICLR 2021
GNNAutoScale: Scalable and Expressive Graph Neural Networks via Historical Embeddings
ICML 2021
Identity-aware Graph Neural Networks
AAAI 2021
Inductive Representation Learning in Temporal Networks via Causal Anonymous Walks
ICLR 2021
Language-Agnostic Representation Learning of Source Code from Structure and Context
ICLR 2021
LEGO: Latent Execution-Guided Reasoning for Multi-Hop Question Answering on Knowledge Graphs
ICML 2021
LM-Critic: Language Models for Unsupervised Grammatical Error Correction
EMNLP 2021
Modeling Heterogeneous Hierarchies with Relation-specific Hyperbolic Cones
NeurIPS 2021
Multi-hop Attention Graph Neural Networks
IJCAI 2021
Neural Distance Embeddings for Biological Sequences
NeurIPS 2021
QA-GNN: Reasoning with Language Models and Knowledge Graphs for Question Answering
NAACL 2021
WILDS: A Benchmark of in-the-Wild Distribution Shifts
ICML 2021
Beta Embeddings for Multi-Hop Logical Reasoning in Knowledge Graphs
NeurIPS 2020
Coresets for Data-efficient Training of Machine Learning Models
ICML 2020
Coresets for Robust Training of Deep Neural Networks against Noisy Labels
NeurIPS 2020
Design Space for Graph Neural Networks
NeurIPS 2020
Distance Encoding: Design Provably More Powerful Neural Networks for Graph Representation Learning
NeurIPS 2020
Graph Information Bottleneck
NeurIPS 2020
Graph Structure of Neural Networks
ICML 2020
Handling Missing Data with Graph Representation Learning
NeurIPS 2020
Learning to Simulate Complex Physics with Graph Networks
ICML 2020
OCEAN: Online Task Inference for Compositional Tasks with Context Adaptation
UAI 2020
Open Graph Benchmark: Datasets for Machine Learning on Graphs
NeurIPS 2020
Query2box: Reasoning over Knowledge Graphs in Vector Space Using Box Embeddings
ICLR 2020
Selection via Proxy: Efficient Data Selection for Deep Learning
ICLR 2020
Strategies for Pre-training Graph Neural Networks
ICLR 2020
Complete the Look: Scene-Based Complementary Product Recommendation
CVPR 2019
G2SAT: Learning to Generate SAT Formulas
NeurIPS 2019
GNNExplainer: Generating Explanations for Graph Neural Networks
NeurIPS 2019
How Powerful are Graph Neural Networks?
ICLR 2019
Hyperbolic Graph Convolutional Neural Networks
NeurIPS 2019
Inferring Multidimensional Rates of Aging from Cross-Sectional Data
AISTATS 2019
Position-aware Graph Neural Networks
ICML 2019
Predicting dominance in multi-person videos
IJCAI 2019
Predicting the Visual Focus of Attention in Multi-Person Discussion Videos
IJCAI 2019
SAGE: A Hybrid Geopolitical Event Forecasting System
IJCAI 2019
Dynamic Network Model from Partial Observations
NeurIPS 2018
Embedding Logical Queries on Knowledge Graphs
NeurIPS 2018
Graph Convolutional Policy Network for Goal-Directed Molecular Graph Generation
NeurIPS 2018
GraphRNN: Generating Realistic Graphs with Deep Auto-regressive Models
ICML 2018
Hierarchical Graph Representation Learning with Differentiable Pooling
NeurIPS 2018
Toeplitz Inverse Covariance-based Clustering of Multivariate Time Series Data
IJCAI 2018
Inductive Representation Learning on Large Graphs
NeurIPS 2017
Learning the Network Structure of Heterogeneous Data via Pairwise Exponential Markov Random Fields
AISTATS 2017
SnapVX: A Network-Based Convex Optimization Solver
JMLR 2017
Confusions over Time: An Interpretable Bayesian Model to Characterize Trends in Decision Making
NeurIPS 2016
Cultural Shift or Linguistic Drift? Comparing Two Computational Measures of Semantic Change
EMNLP 2016
Diachronic Word Embeddings Reveal Statistical Laws of Semantic Change
ACL 2016
Inducing Domain-Specific Sentiment Lexicons from Unlabeled Corpora
EMNLP 2016
A computational approach to politeness with application to social factors
ACL 2013
Modeling Information Propagation with Survival Theory
ICML 2013
Nonparametric Multi-group Membership Model for Dynamic Networks
NeurIPS 2013
Learning to Discover Social Circles in Ego Networks
NeurIPS 2012
Kronecker Graphs: An Approach to Modeling Networks
JMLR 2010
On the Convexity of Latent Social Network Inference
NeurIPS 2010