William L. Hamilton

According to our database, William L. Hamilton authored at least 69 papers between 2013 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Generative Active Learning for the Search of Small-molecule Protein Binders.

Maksym Korablyov, Cheng-Hao Liu, Moksh Jain, Almer M. van der Sloot, Eric Jolicoeur, Edward Ruediger, Andrei Cristian Nica, Emmanuel Bengio, Kostiantyn Lapchevskyi, Daniel St-Cyr, Doris Alexandra Schuetz, Victor Ion Butoi, Jarrid Rector-Brooks, Simon Blackburn, Leo Feng, Hadi Nekoei, Sai Krishna Gottipati, Priyesh Vijayan, Prateek Gupta, Ladislav Rampásek, Sasikanth Avancha, Pierre-Luc Bacon, William L. Hamilton, Brooks Paige, Sanchit Misra, Stanislaw Kamil Jastrzebski, Bharat Kaul, Doina Precup, José Miguel Hernández-Lobato, Marwin H. S. Segler, Michael M. Bronstein, Anne Marinier, Mike Tyers, Yoshua Bengio

CoRR, 2024

2023

Bombardier Aftermarket Demand Forecast with Machine Learning.

Pierre Dodin, Jingyi Xiao, Yossiri Adulyasak, Neda Etebari Alamdari, Lea Gauthier, Philippe Grangier, Paul Lemaître, William L. Hamilton

INFORMS J. Appl. Anal., 2023

2022

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

Carlos G. Oliver, Vincent Mallet, Pericles Philippopoulos, William L. Hamilton, Jérôme Waldispühl

Bioinform., 2022

RNAglib: a python package for RNA 2.5 D graphs.

Vincent Mallet, Carlos G. Oliver, Jonathan Broadbent, William L. Hamilton, Jérôme Waldispühl

Bioinform., 2022

A review of biomedical datasets relating to drug discovery: a knowledge graph perspective.

Stephen Bonner, Ian P. Barrett, Cheng Ye, Rowan Swiers, Ola Engkvist, Andreas Bender, Charles Tapley Hoyt, William L. Hamilton

Briefings Bioinform., 2022

Online Adversarial Attacks.

Andjela Mladenovic, Avishek Joey Bose, Hugo Berard, William L. Hamilton, Simon Lacoste-Julien, Pascal Vincent, Gauthier Gidel

Proceedings of the Tenth International Conference on Learning Representations, 2022

NodePiece: Compositional and Parameter-Efficient Representations of Large Knowledge Graphs.

Mikhail Galkin, Etienne G. Denis, Jiapeng Wu, William L. Hamilton

Proceedings of the Tenth International Conference on Learning Representations, 2022

2021

Edge-similarity-aware Graph Neural Networks.

Vincent Mallet, Carlos G. Oliver, William L. Hamilton

CoRR, 2021

Understanding the Performance of Knowledge Graph Embeddings in Drug Discovery.

Stephen Bonner, Ian P. Barrett, Cheng Ye, Rowan Swiers, Ola Engkvist, William L. Hamilton

CoRR, 2021

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

Stephen Bonner, Ian P. Barrett, Cheng Ye, Rowan Swiers, Ola Engkvist, Andreas Bender, William L. Hamilton

CoRR, 2021

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

Greta Laage, Emma Frejinger, William L. Hamilton, Andrea Lodi, Guillaume Rabusseau

CoRR, 2021

End-to-End Training of Multi-Document Reader and Retriever for Open-Domain Question Answering.

Devendra Singh Sachan, Siva Reddy, William L. Hamilton, Chris Dyer, Dani Yogatama

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.

Devin Kreuzer, Dominique Beaini, William L. Hamilton, Vincent Létourneau, Prudencio Tossou

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Directional Graph Networks.

Dominique Beaini, Saro Passaro, Vincent Létourneau, William L. Hamilton, Gabriele Corso, Pietro Lió

Proceedings of the 38th International Conference on Machine Learning, 2021

Neural representation and generation for RNA secondary structures.

Zichao Yan, William L. Hamilton, Mathieu Blanchette

Proceedings of the 9th International Conference on Learning Representations, 2021

A Universal Representation Transformer Layer for Few-Shot Image Classification.

Lu Liu, William L. Hamilton, Guodong Long, Jing Jiang, Hugo Larochelle

Proceedings of the 9th International Conference on Learning Representations, 2021

Ego-GNNs: Exploiting Ego Structures in Graph Neural Networks.

Dylan Sandfelder, Priyesh Vijayan, William L. Hamilton

Proceedings of the IEEE International Conference on Acoustics, 2021

Do Syntax Trees Help Pre-trained Transformers Extract Information?

Devendra Singh Sachan, Yuhao Zhang, Peng Qi, William L. Hamilton

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.

Dora Jambor, Komal K. Teru, Joelle Pineau, William L. Hamilton

Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Main Volume, 2021

Structural Inductive Biases in Emergent Communication.

Agnieszka Slowik, Abhinav Gupta, William L. Hamilton, Mateja Jamnik, Sean B. Holden, Chris Pal

Proceedings of the 43rd Annual Meeting of the Cognitive Science Society, 2021

End-to-End Training of Neural Retrievers for Open-Domain Question Answering.

Devendra Singh Sachan, Mostofa Patwary, Mohammad Shoeybi, Neel Kant, Wei Ping, William L. Hamilton, Bryan Catanzaro

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

William L. Hamilton

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.

Devendra Singh Sachan, Lingfei Wu, Mrinmaya Sachan, William L. Hamilton

CoRR, 2020

Evaluating Logical Generalization in Graph Neural Networks.

Koustuv Sinha, Shagun Sodhani, Joelle Pineau, William L. Hamilton

CoRR, 2020

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

Ashutosh Adhikari, Xingdi Yuan, Marc-Alexandre Côté, Mikulas Zelinka, Marc-Antoine Rondeau, Romain Laroche, Pascal Poupart, Jian Tang, Adam Trischler, William L. Hamilton

CoRR, 2020

Exploring Structural Inductive Biases in Emergent Communication.

Agnieszka Slowik, Abhinav Gupta, William L. Hamilton, Mateja Jamnik, Sean B. Holden, Christopher J. Pal

CoRR, 2020

Towards Graph Representation Learning in Emergent Communication.

Agnieszka Slowik, Abhinav Gupta, William L. Hamilton, Mateja Jamnik, Sean B. Holden

CoRR, 2020

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

Zichao Yan, William L. Hamilton, Mathieu Blanchette

Bioinform., 2020

Exploring the Limits of Simple Learners in Knowledge Distillation for Document Classification with DocBERT.

Ashutosh Adhikari, Achyudh Ram, Raphael Tang, William L. Hamilton, Jimmy Lin

Proceedings of the 5th Workshop on Representation Learning for NLP, 2020

Adversarial Example Games.

Avishek Joey Bose, Gauthier Gidel, Hugo Berard, Andre Cianflone, Pascal Vincent, Simon Lacoste-Julien, William L. Hamilton

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.

Ashutosh Adhikari, Xingdi Yuan, Marc-Alexandre Côté, Mikulas Zelinka, Marc-Antoine Rondeau, Romain Laroche, Pascal Poupart, Jian Tang, Adam Trischler, William L. Hamilton

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.

Komal K. Teru, Etienne G. Denis, William L. Hamilton

Proceedings of the 37th International Conference on Machine Learning, 2020

Latent Variable Modelling with Hyperbolic Normalizing Flows.

Avishek Joey Bose, Ariella Smofsky, Renjie Liao, Prakash Panangaden, William L. Hamilton

Proceedings of the 37th International Conference on Machine Learning, 2020

TeMP: Temporal Message Passing for Temporal Knowledge Graph Completion.

Jiapeng Wu, Meng Cao, Jackie Chi Kit Cheung, William L. Hamilton

Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing, 2020

Distilling Structured Knowledge for Text-Based Relational Reasoning.

Jin Dong, Marc-Antoine Rondeau, William L. Hamilton

Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing, 2020

Structure Aware Negative Sampling in Knowledge Graphs.

Kian Ahrabian, Aarash Feizi, Yasmin Salehi, William L. Hamilton, Avishek Joey Bose

Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing, 2020

Learning an Unreferenced Metric for Online Dialogue Evaluation.

Koustuv Sinha, Prasanna Parthasarathi, Jasmine Wang, Ryan Lowe, William L. Hamilton, Joelle Pineau

Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, 2020

2019

Meta-Graph: Few shot Link Prediction via Meta Learning.

Avishek Joey Bose, Ankit Jain, Piero Molino, William L. Hamilton

CoRR, 2019

Inductive Relation Prediction on Knowledge Graphs.

Komal K. Teru, William L. Hamilton

CoRR, 2019

Actor Critic with Differentially Private Critic.

Jonathan Lebensold, William L. Hamilton, Borja Balle, Doina Precup

CoRR, 2019

Efficient Graph Generation with Graph Recurrent Attention Networks.

Renjie Liao, Yujia Li, Yang Song, Shenlong Wang, Charlie Nash, William L. Hamilton, David Duvenaud, Raquel Urtasun, Richard S. Zemel

CoRR, 2019

Generalizable Adversarial Attacks Using Generative Models.

Avishek Joey Bose, Andre Cianflone, William L. Hamilton

CoRR, 2019

Efficient Graph Generation with Graph Recurrent Attention Networks.

Renjie Liao, Yujia Li, Yang Song, Shenlong Wang, William L. Hamilton, David Duvenaud, Raquel Urtasun, Richard S. Zemel

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.

Charles C. Onu, Jonathan Lebensold, William L. Hamilton, Doina Precup

Proceedings of the 20th Annual Conference of the International Speech Communication Association, 2019

Compositional Fairness Constraints for Graph Embeddings.

Avishek Joey Bose, William L. Hamilton

Proceedings of the 36th International Conference on Machine Learning, 2019

Deep Graph Infomax.

Petar Velickovic, William Fedus, William L. Hamilton, Pietro Liò, Yoshua Bengio, R. Devon Hjelm

Proceedings of the 7th International Conference on Learning Representations, 2019

CLUTRR: A Diagnostic Benchmark for Inductive Reasoning from Text.

Koustuv Sinha, Shagun Sodhani, Jin Dong, Joelle Pineau, William L. Hamilton

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.

Christopher Morris, Martin Ritzert, Matthias Fey, William L. Hamilton, Jan Eric Lenssen, Gaurav Rattan, Martin Grohe

Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

2018

Representation learning methods for computational social science.

William L. Hamilton

PhD thesis, 2018

Compositional Language Understanding with Text-based Relational Reasoning.

Koustuv Sinha, Shagun Sodhani, William L. Hamilton, Joelle Pineau

CoRR, 2018

Querying Complex Networks in Vector Space.

William L. Hamilton, Payal Bajaj, Marinka Zitnik, Dan Jurafsky, Jure Leskovec

CoRR, 2018

GraphRNN: A Deep Generative Model for Graphs.

Jiaxuan You, Rex Ying, Xiang Ren, William L. Hamilton, Jure Leskovec

CoRR, 2018

Community Interaction and Conflict on the Web.

Srijan Kumar, William L. Hamilton, Jure Leskovec, Dan Jurafsky

Proceedings of the 2018 World Wide Web Conference on World Wide Web, 2018

Hierarchical Graph Representation Learning with Differentiable Pooling.

Zhitao Ying, Jiaxuan You, Christopher Morris, Xiang Ren, William L. Hamilton, Jure Leskovec

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.

William L. Hamilton, Payal Bajaj, Marinka Zitnik, Dan Jurafsky, Jure Leskovec

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.

Rex Ying, Ruining He, Kaifeng Chen, Pong Eksombatchai, William L. Hamilton, Jure Leskovec

Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2018

GraphRNN: Generating Realistic Graphs with Deep Auto-regressive Models.

Jiaxuan You, Rex Ying, Xiang Ren, William L. Hamilton, Jure Leskovec

Proceedings of the 35th International Conference on Machine Learning, 2018

2017

Representation Learning on Graphs: Methods and Applications.

William L. Hamilton, Rex Ying, Jure Leskovec

IEEE Data Eng. Bull., 2017

Inductive Representation Learning on Large Graphs.

William L. Hamilton, Zhitao Ying, Jure Leskovec

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.

Justine Zhang, William L. Hamilton, Cristian Danescu-Niculescu-Mizil, Dan Jurafsky, Jure Leskovec

Proceedings of the Eleventh International Conference on Web and Social Media, 2017

Loyalty in Online Communities.

William L. Hamilton, Justine Zhang, Cristian Danescu-Niculescu-Mizil, Dan Jurafsky, Jure Leskovec

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.

William L. Hamilton, Jure Leskovec, Dan Jurafsky

Proceedings of the 2016 Conference on Empirical Methods in Natural Language Processing, 2016

Inducing Domain-Specific Sentiment Lexicons from Unlabeled Corpora.

William L. Hamilton, Kevin Clark, Jure Leskovec, Dan Jurafsky

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.

Vinodkumar Prabhakaran, William L. Hamilton, Daniel A. McFarland, Dan Jurafsky

Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics, 2016

Diachronic Word Embeddings Reveal Statistical Laws of Semantic Change.

William L. Hamilton, Jure Leskovec, Dan Jurafsky

Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics, 2016

Learning Linguistic Descriptors of User Roles in Online Communities.

Alex Wang, William L. Hamilton, Jure Leskovec

Proceedings of the First Workshop on NLP and Computational Social Science, 2016

2014

Efficient learning and planning with compressed predictive states.

William L. Hamilton, Mahdi Milani Fard, Joelle Pineau

J. Mach. Learn. Res., 2014

Methods of Moments for Learning Stochastic Languages: Unified Presentation and Empirical Comparison.

Borja Balle, William L. Hamilton, Joelle Pineau

Proceedings of the 31th International Conference on Machine Learning, 2014

2013

Modelling Sparse Dynamical Systems with Compressed Predictive State Representations.

William L. Hamilton, Mahdi Milani Fard, Joelle Pineau

Proceedings of the 30th International Conference on Machine Learning, 2013