William L. Hamilton

Affiliations:
  • Mila - Quebec AI Institute, Montréal, QC, Canada
  • McGill University, Montréal, QC, Canada
  • Stanford University, Stanford, CA, USA (former)


According to our database1, William L. Hamilton authored at least 67 papers between 2013 and 2022.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Bibliography

2022
Vernal: a tool for mining fuzzy network motifs in RNA.
Bioinform., 2022

RNAglib: a python package for RNA 2.5 D graphs.
Bioinform., 2022

A review of biomedical datasets relating to drug discovery: a knowledge graph perspective.
Briefings Bioinform., 2022

Online Adversarial Attacks.
Proceedings of the Tenth International Conference on Learning Representations, 2022

NodePiece: Compositional and Parameter-Efficient Representations of Large Knowledge Graphs.
Proceedings of the Tenth International Conference on Learning Representations, 2022

2021
Edge-similarity-aware Graph Neural Networks.
CoRR, 2021

Understanding the Performance of Knowledge Graph Embeddings in Drug Discovery.
CoRR, 2021

A Review of Biomedical Datasets Relating to Drug Discovery: A Knowledge Graph Perspective.
CoRR, 2021

Estimating the Impact of an Improvement to a Revenue Management System: An Airline Application.
CoRR, 2021

End-to-End Training of Multi-Document Reader and Retriever for Open-Domain Question Answering.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Rethinking Graph Transformers with Spectral Attention.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Directional Graph Networks.
Proceedings of the 38th International Conference on Machine Learning, 2021

Neural representation and generation for RNA secondary structures.
Proceedings of the 9th International Conference on Learning Representations, 2021

A Universal Representation Transformer Layer for Few-Shot Image Classification.
Proceedings of the 9th International Conference on Learning Representations, 2021

Ego-GNNs: Exploiting Ego Structures in Graph Neural Networks.
Proceedings of the IEEE International Conference on Acoustics, 2021

Do Syntax Trees Help Pre-trained Transformers Extract Information?
Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Main Volume, 2021

Exploring the Limits of Few-Shot Link Prediction in Knowledge Graphs.
Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Main Volume, 2021

Structural Inductive Biases in Emergent Communication.
Proceedings of the 43th Annual Meeting of the Cognitive Science Society, 2021

End-to-End Training of Neural Retrievers for Open-Domain Question Answering.
Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing, 2021

2020
Graph Representation Learning
Synthesis Lectures on Artificial Intelligence and Machine Learning, Morgan & Claypool Publishers, ISBN: 978-3-031-01588-5, 2020

Stronger Transformers for Neural Multi-Hop Question Generation.
CoRR, 2020

Evaluating Logical Generalization in Graph Neural Networks.
CoRR, 2020

Learning Dynamic Knowledge Graphs to Generalize on Text-Based Games.
CoRR, 2020

Exploring Structural Inductive Biases in Emergent Communication.
CoRR, 2020

Towards Graph Representation Learning in Emergent Communication.
CoRR, 2020

Graph neural representational learning of RNA secondary structures for predicting RNA-protein interactions.
Bioinform., 2020

Exploring the Limits of Simple Learners in Knowledge Distillation for Document Classification with DocBERT.
Proceedings of the 5th Workshop on Representation Learning for NLP, 2020

Adversarial Example Games.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Learning Dynamic Belief Graphs to Generalize on Text-Based Games.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Inductive Relation Prediction by Subgraph Reasoning.
Proceedings of the 37th International Conference on Machine Learning, 2020

Latent Variable Modelling with Hyperbolic Normalizing Flows.
Proceedings of the 37th International Conference on Machine Learning, 2020

TeMP: Temporal Message Passing for Temporal Knowledge Graph Completion.
Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing, 2020

Distilling Structured Knowledge for Text-Based Relational Reasoning.
Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing, 2020

Structure Aware Negative Sampling in Knowledge Graphs.
Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing, 2020

Learning an Unreferenced Metric for Online Dialogue Evaluation.
Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, 2020

2019
Meta-Graph: Few shot Link Prediction via Meta Learning.
CoRR, 2019

Inductive Relation Prediction on Knowledge Graphs.
CoRR, 2019

Actor Critic with Differentially Private Critic.
CoRR, 2019

Efficient Graph Generation with Graph Recurrent Attention Networks.
CoRR, 2019

Generalizable Adversarial Attacks Using Generative Models.
CoRR, 2019

Efficient Graph Generation with Graph Recurrent Attention Networks.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Neural Transfer Learning for Cry-Based Diagnosis of Perinatal Asphyxia.
Proceedings of the Interspeech 2019, 2019

Compositional Fairness Constraints for Graph Embeddings.
Proceedings of the 36th International Conference on Machine Learning, 2019

Deep Graph Infomax.
Proceedings of the 7th International Conference on Learning Representations, 2019

CLUTRR: A Diagnostic Benchmark for Inductive Reasoning from Text.
Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing, 2019

Weisfeiler and Leman Go Neural: Higher-Order Graph Neural Networks.
Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

2018
Representation learning methods for computational social science.
PhD thesis, 2018

Compositional Language Understanding with Text-based Relational Reasoning.
CoRR, 2018

Querying Complex Networks in Vector Space.
CoRR, 2018

GraphRNN: A Deep Generative Model for Graphs.
CoRR, 2018

Community Interaction and Conflict on the Web.
Proceedings of the 2018 World Wide Web Conference on World Wide Web, 2018

Hierarchical Graph Representation Learning with Differentiable Pooling.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Embedding Logical Queries on Knowledge Graphs.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Graph Convolutional Neural Networks for Web-Scale Recommender Systems.
Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2018

GraphRNN: Generating Realistic Graphs with Deep Auto-regressive Models.
Proceedings of the 35th International Conference on Machine Learning, 2018

2017
Representation Learning on Graphs: Methods and Applications.
IEEE Data Eng. Bull., 2017

Inductive Representation Learning on Large Graphs.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Community Identity and User Engagement in a Multi-Community Landscape.
Proceedings of the Eleventh International Conference on Web and Social Media, 2017

Loyalty in Online Communities.
Proceedings of the Eleventh International Conference on Web and Social Media, 2017

2016
Cultural Shift or Linguistic Drift? Comparing Two Computational Measures of Semantic Change.
Proceedings of the 2016 Conference on Empirical Methods in Natural Language Processing, 2016

Inducing Domain-Specific Sentiment Lexicons from Unlabeled Corpora.
Proceedings of the 2016 Conference on Empirical Methods in Natural Language Processing, 2016

Predicting the Rise and Fall of Scientific Topics from Trends in their Rhetorical Framing.
Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics, 2016

Diachronic Word Embeddings Reveal Statistical Laws of Semantic Change.
Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics, 2016

Learning Linguistic Descriptors of User Roles in Online Communities.
Proceedings of the First Workshop on NLP and Computational Social Science, 2016

2014
Efficient learning and planning with compressed predictive states.
J. Mach. Learn. Res., 2014

Methods of Moments for Learning Stochastic Languages: Unified Presentation and Empirical Comparison.
Proceedings of the 31th International Conference on Machine Learning, 2014

2013
Modelling Sparse Dynamical Systems with Compressed Predictive State Representations.
Proceedings of the 30th International Conference on Machine Learning, 2013


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