William L. Hamilton

Publication Activity (10 Years)

Years Active: 2013-2024
Publications (10 Years): 95

Top Topics

Temporal Knowledge

Graph Representation

Top Venues

Publications

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
Generative Active Learning for the Search of Small-molecule Protein Binders. CoRR (2024)
Pierre Dodin, Jingyi Xiao, Yossiri Adulyasak, Neda Etebari Alamdari, Lea Gauthier, Philippe Grangier, Paul Lemaître, William L. Hamilton
Bombardier Aftermarket Demand Forecast with Machine Learning. INFORMS J. Appl. Anal. 53 (6) (2023)
Andjela Mladenovic, Avishek Joey Bose, Hugo Berard, William L. Hamilton, Simon Lacoste-Julien, Pascal Vincent, Gauthier Gidel
Online Adversarial Attacks. ICLR (2022)
Mikhail Galkin, Etienne G. Denis, Jiapeng Wu, William L. Hamilton
NodePiece: Compositional and Parameter-Efficient Representations of Large Knowledge Graphs. ICLR (2022)
Vincent Mallet, Carlos G. Oliver, Jonathan Broadbent, William L. Hamilton, Jérôme Waldispühl
RNAglib: a python package for RNA 2.5 D graphs. Bioinform. 38 (5) (2022)
Stephen Bonner, Ian P. Barrett, Cheng Ye, Rowan Swiers, Ola Engkvist, Andreas Bender, Charles Tapley Hoyt, William L. Hamilton
A review of biomedical datasets relating to drug discovery: a knowledge graph perspective. Briefings Bioinform. 23 (6) (2022)
Carlos G. Oliver, Vincent Mallet, Pericles Philippopoulos, William L. Hamilton, Jérôme Waldispühl
Vernal: a tool for mining fuzzy network motifs in RNA. Bioinform. 38 (4) (2022)
Stephen Bonner, Ian P. Barrett, Cheng Ye, Rowan Swiers, Ola Engkvist, William L. Hamilton
Understanding the Performance of Knowledge Graph Embeddings in Drug Discovery. CoRR (2021)
Zichao Yan, William L. Hamilton, Mathieu Blanchette
Neural representation and generation for RNA secondary structures. ICLR (2021)
Devendra Singh Sachan, Yuhao Zhang, Peng Qi, William L. Hamilton
Do Syntax Trees Help Pre-trained Transformers Extract Information? EACL (2021)
Agnieszka Slowik, Abhinav Gupta, William L. Hamilton, Mateja Jamnik, Sean B. Holden, Chris Pal
Structural Inductive Biases in Emergent Communication. CogSci (2021)
Devin Kreuzer, Dominique Beaini, William L. Hamilton, Vincent Létourneau, Prudencio Tossou
Rethinking Graph Transformers with Spectral Attention. NeurIPS (2021)
Dylan Sandfelder, Priyesh Vijayan, William L. Hamilton
Ego-GNNs: Exploiting Ego Structures in Graph Neural Networks. CoRR (2021)
Devendra Singh Sachan, Siva Reddy, William L. Hamilton, Chris Dyer, Dani Yogatama
End-to-End Training of Multi-Document Reader and Retriever for Open-Domain Question Answering. CoRR (2021)
Devin Kreuzer, Dominique Beaini, William L. Hamilton, Vincent Létourneau, Prudencio Tossou
Rethinking Graph Transformers with Spectral Attention. CoRR (2021)
Devendra Singh Sachan, Mostofa Patwary, Mohammad Shoeybi, Neel Kant, Wei Ping, William L. Hamilton, Bryan Catanzaro
End-to-End Training of Neural Retrievers for Open-Domain Question Answering. CoRR (2021)
Dominique Beaini, Saro Passaro, Vincent Létourneau, William L. Hamilton, Gabriele Corso, Pietro Lió
Directional Graph Networks. ICML (2021)
Devendra Singh Sachan, Siva Reddy, William L. Hamilton, Chris Dyer, Dani Yogatama
End-to-End Training of Multi-Document Reader and Retriever for Open-Domain Question Answering. NeurIPS (2021)
Lu Liu, William L. Hamilton, Guodong Long, Jing Jiang, Hugo Larochelle
A Universal Representation Transformer Layer for Few-Shot Image Classification. ICLR (2021)
Zichao Yan, William L. Hamilton, Mathieu Blanchette
Neural representation and generation for RNA secondary structures. CoRR (2021)
Andjela Mladenovic, Avishek Joey Bose, Hugo Berard, William L. Hamilton, Simon Lacoste-Julien, Pascal Vincent, Gauthier Gidel
Online Adversarial Attacks. CoRR (2021)
Stephen Bonner, Ian P. Barrett, Cheng Ye, Rowan Swiers, Ola Engkvist, Andreas Bender, William L. Hamilton
A Review of Biomedical Datasets Relating to Drug Discovery: A Knowledge Graph Perspective. CoRR (2021)
Mikhail Galkin, Jiapeng Wu, Etienne Denis, William L. Hamilton
NodePiece: Compositional and Parameter-Efficient Representations of Large Knowledge Graphs. CoRR (2021)
Devendra Singh Sachan, Mostofa Patwary, Mohammad Shoeybi, Neel Kant, Wei Ping, William L. Hamilton, Bryan Catanzaro
End-to-End Training of Neural Retrievers for Open-Domain Question Answering. ACL/IJCNLP (1) (2021)
Dora Jambor, Komal K. Teru, Joelle Pineau, William L. Hamilton
Exploring the Limits of Few-Shot Link Prediction in Knowledge Graphs. CoRR (2021)
Dora Jambor, Komal K. Teru, Joelle Pineau, William L. Hamilton
Exploring the Limits of Few-Shot Link Prediction in Knowledge Graphs. EACL (2021)
Greta Laage, Emma Frejinger, William L. Hamilton, Andrea Lodi, Guillaume Rabusseau
Estimating the Impact of an Improvement to a Revenue Management System: An Airline Application. CoRR (2021)
Dylan Sandfelder, Priyesh Vijayan, William L. Hamilton
Ego-GNNs: Exploiting Ego Structures in Graph Neural Networks. ICASSP (2021)
Vincent Mallet, Carlos G. Oliver, William L. Hamilton
Edge-similarity-aware Graph Neural Networks. CoRR (2021)
Kian Ahrabian, Aarash Feizi, Yasmin Salehi, William L. Hamilton, Avishek Joey Bose
Structure Aware Negative Sampling in Knowledge Graphs. CoRR (2020)
Avishek Joey Bose, Ariella Smofsky, Renjie Liao, Prakash Panangaden, William L. Hamilton
Latent Variable Modelling with Hyperbolic Normalizing Flows. ICML (2020)
Ashutosh Adhikari, Achyudh Ram, Raphael Tang, William L. Hamilton, Jimmy Lin
Exploring the Limits of Simple Learners in Knowledge Distillation for Document Classification with DocBERT. RepL4NLP@ACL (2020)
Devendra Singh Sachan, Yuhao Zhang, Peng Qi, William L. Hamilton
Do Syntax Trees Help Pre-trained Transformers Extract Information? CoRR (2020)
Dominique Beaini, Saro Passaro, Vincent Létourneau, William L. Hamilton, Gabriele Corso, Pietro Liò
Directional Graph Networks. CoRR (2020)
Devendra Singh Sachan, Lingfei Wu, Mrinmaya Sachan, William L. Hamilton
Stronger Transformers for Neural Multi-Hop Question Generation. CoRR (2020)
Jin Dong, Marc-Antoine Rondeau, William L. Hamilton
Distilling Structured Knowledge for Text-Based Relational Reasoning. EMNLP (1) (2020)
Lu Liu, William L. Hamilton, Guodong Long, Jing Jiang, Hugo Larochelle
A Universal Representation Transformer Layer for Few-Shot Image Classification. CoRR (2020)
Kian Ahrabian, Aarash Feizi, Yasmin Salehi, William L. Hamilton, Avishek Joey Bose
Structure Aware Negative Sampling in Knowledge Graphs. EMNLP (1) (2020)
Koustuv Sinha, Prasanna Parthasarathi, Jasmine Wang, Ryan Lowe, William L. Hamilton, Joelle Pineau
Learning an Unreferenced Metric for Online Dialogue Evaluation. ACL (2020)
Ashutosh Adhikari, Xingdi Yuan, Marc-Alexandre Côté, Mikulas Zelinka, Marc-Antoine Rondeau, Romain Laroche, Pascal Poupart, Jian Tang, Adam Trischler, William L. Hamilton
Learning Dynamic Belief Graphs to Generalize on Text-Based Games. NeurIPS (2020)
Agnieszka Slowik, Abhinav Gupta, William L. Hamilton, Mateja Jamnik, Sean B. Holden, Christopher J. Pal
Exploring Structural Inductive Biases in Emergent Communication. CoRR (2020)
Ashutosh Adhikari, Xingdi Yuan, Marc-Alexandre Côté, Mikulas Zelinka, Marc-Antoine Rondeau, Romain Laroche, Pascal Poupart, Jian Tang, Adam Trischler, William L. Hamilton
Learning Dynamic Knowledge Graphs to Generalize on Text-Based Games. CoRR (2020)
Avishek Joey Bose, Ariella Smofsky, Renjie Liao, Prakash Panangaden, William L. Hamilton
Latent Variable Modelling with Hyperbolic Normalizing Flows. CoRR (2020)
Avishek Joey Bose, Gauthier Gidel, Hugo Berard, Andre Cianflone, Pascal Vincent, Simon Lacoste-Julien, William L. Hamilton
Adversarial Example Games. NeurIPS (2020)
Jiapeng Wu, Meng Cao, Jackie Chi Kit Cheung, William L. Hamilton
TeMP: Temporal Message Passing for Temporal Knowledge Graph Completion. EMNLP (1) (2020)
Koustuv Sinha, Shagun Sodhani, Joelle Pineau, William L. Hamilton
Evaluating Logical Generalization in Graph Neural Networks. CoRR (2020)
Agnieszka Slowik, Abhinav Gupta, William L. Hamilton, Mateja Jamnik, Sean B. Holden
Towards Graph Representation Learning in Emergent Communication. CoRR (2020)
Jiapeng Wu, Meng Cao, Jackie Chi Kit Cheung, William L. Hamilton
TeMP: Temporal Message Passing for Temporal Knowledge Graph Completion. CoRR (2020)
Zichao Yan, William L. Hamilton, Mathieu Blanchette
Graph neural representational learning of RNA secondary structures for predicting RNA-protein interactions. Bioinform. 36 (Supplement-1) (2020)
Carlos G. Oliver, Vincent Mallet, Pericles Philippopoulos, William L. Hamilton, Jérôme Waldispühl
VeRNAl: A Tool for Mining Fuzzy Network Motifs in RNA. CoRR (2020)
Avishek Joey Bose, Gauthier Gidel, Hugo Berard, Andre Cianflone, Pascal Vincent, Simon Lacoste-Julien, William L. Hamilton
Adversarial Example Games. CoRR (2020)
Koustuv Sinha, Prasanna Parthasarathi, Jasmine Wang, Ryan Lowe, William L. Hamilton, Joelle Pineau
Learning an Unreferenced Metric for Online Dialogue Evaluation. CoRR (2020)
Petar Velickovic, William Fedus, William L. Hamilton, Pietro Liò, Yoshua Bengio, R. Devon Hjelm
Deep Graph Infomax. ICLR (Poster) (2019)
Christopher Morris, Martin Ritzert, Matthias Fey, William L. Hamilton, Jan Eric Lenssen, Gaurav Rattan, Martin Grohe
Weisfeiler and Leman Go Neural: Higher-Order Graph Neural Networks. AAAI (2019)
Avishek Joey Bose, Ankit Jain, Piero Molino, William L. Hamilton
Meta-Graph: Few shot Link Prediction via Meta Learning. CoRR (2019)
Charles C. Onu, Jonathan Lebensold, William L. Hamilton, Doina Precup
Neural Transfer Learning for Cry-based Diagnosis of Perinatal Asphyxia. CoRR (2019)
Avishek Joey Bose, William L. Hamilton
Compositional Fairness Constraints for Graph Embeddings. ICML (2019)
Charles C. Onu, Jonathan Lebensold, William L. Hamilton, Doina Precup
Neural Transfer Learning for Cry-Based Diagnosis of Perinatal Asphyxia. INTERSPEECH (2019)
Avishek Joey Bose, Andre Cianflone, William L. Hamilton
Generalizable Adversarial Attacks Using Generative Models. CoRR (2019)
Koustuv Sinha, Shagun Sodhani, Jin Dong, Joelle Pineau, William L. Hamilton
CLUTRR: A Diagnostic Benchmark for Inductive Reasoning from Text. CoRR (2019)
Renjie Liao, Yujia Li, Yang Song, Shenlong Wang, Charlie Nash, William L. Hamilton, David Duvenaud, Raquel Urtasun, Richard S. Zemel
Efficient Graph Generation with Graph Recurrent Attention Networks. CoRR (2019)
Komal K. Teru, William L. Hamilton
Inductive Relation Prediction on Knowledge Graphs. CoRR (2019)
Koustuv Sinha, Shagun Sodhani, Jin Dong, Joelle Pineau, William L. Hamilton
CLUTRR: A Diagnostic Benchmark for Inductive Reasoning from Text. EMNLP/IJCNLP (1) (2019)
Jonathan Lebensold, William L. Hamilton, Borja Balle, Doina Precup
Actor Critic with Differentially Private Critic. CoRR (2019)
Avishek Joey Bose, William L. Hamilton
Compositional Fairness Constraints for Graph Embeddings. CoRR (2019)
Renjie Liao, Yujia Li, Yang Song, Shenlong Wang, William L. Hamilton, David Duvenaud, Raquel Urtasun, Richard S. Zemel
Efficient Graph Generation with Graph Recurrent Attention Networks. NeurIPS (2019)
Rex Ying, Ruining He, Kaifeng Chen, Pong Eksombatchai, William L. Hamilton, Jure Leskovec
Graph Convolutional Neural Networks for Web-Scale Recommender Systems. KDD (2018)
William L. Hamilton, Payal Bajaj, Marinka Zitnik, Dan Jurafsky, Jure Leskovec
Querying Complex Networks in Vector Space. CoRR (2018)
Rex Ying, Jiaxuan You, Christopher Morris, Xiang Ren, William L. Hamilton, Jure Leskovec
Hierarchical Graph Representation Learning with Differentiable Pooling. CoRR (2018)
Rex Ying, Ruining He, Kaifeng Chen, Pong Eksombatchai, William L. Hamilton, Jure Leskovec
Graph Convolutional Neural Networks for Web-Scale Recommender Systems. CoRR (2018)
Petar Velickovic, William Fedus, William L. Hamilton, Pietro Liò, Yoshua Bengio, R. Devon Hjelm
Deep Graph Infomax. CoRR (2018)
Srijan Kumar, William L. Hamilton, Jure Leskovec, Dan Jurafsky
Community Interaction and Conflict on the Web. WWW (2018)
Christopher Morris, Martin Ritzert, Matthias Fey, William L. Hamilton, Jan Eric Lenssen, Gaurav Rattan, Martin Grohe
Weisfeiler and Leman Go Neural: Higher-order Graph Neural Networks. CoRR (2018)
Koustuv Sinha, Shagun Sodhani, William L. Hamilton, Joelle Pineau
Compositional Language Understanding with Text-based Relational Reasoning. CoRR (2018)
Srijan Kumar, William L. Hamilton, Jure Leskovec, Dan Jurafsky
Community Interaction and Conflict on the Web. CoRR (2018)
Zhitao Ying, Jiaxuan You, Christopher Morris, Xiang Ren, William L. Hamilton, Jure Leskovec
Hierarchical Graph Representation Learning with Differentiable Pooling. NeurIPS (2018)
Jiaxuan You, Rex Ying, Xiang Ren, William L. Hamilton, Jure Leskovec
GraphRNN: A Deep Generative Model for Graphs. CoRR (2018)
William L. Hamilton, Payal Bajaj, Marinka Zitnik, Dan Jurafsky, Jure Leskovec
Embedding Logical Queries on Knowledge Graphs. NeurIPS (2018)
Jiaxuan You, Rex Ying, Xiang Ren, William L. Hamilton, Jure Leskovec
GraphRNN: Generating Realistic Graphs with Deep Auto-regressive Models. ICML (2018)
William L. Hamilton, Zhitao Ying, Jure Leskovec
Inductive Representation Learning on Large Graphs. NIPS (2017)
William L. Hamilton, Justine Zhang, Cristian Danescu-Niculescu-Mizil, Dan Jurafsky, Jure Leskovec
Loyalty in Online Communities. ICWSM (2017)
Justine Zhang, William L. Hamilton, Cristian Danescu-Niculescu-Mizil, Dan Jurafsky, Jure Leskovec
Community Identity and User Engagement in a Multi-Community Landscape. CoRR (2017)
William L. Hamilton, Justine Zhang, Cristian Danescu-Niculescu-Mizil, Dan Jurafsky, Jure Leskovec
Loyalty in Online Communities. CoRR (2017)
Justine Zhang, William L. Hamilton, Cristian Danescu-Niculescu-Mizil, Dan Jurafsky, Jure Leskovec
Community Identity and User Engagement in a Multi-Community Landscape. ICWSM (2017)
William L. Hamilton, Rex Ying, Jure Leskovec
Inductive Representation Learning on Large Graphs. CoRR (2017)
William L. Hamilton, Rex Ying, Jure Leskovec
Representation Learning on Graphs: Methods and Applications. IEEE Data Eng. Bull. 40 (3) (2017)
William L. Hamilton, Rex Ying, Jure Leskovec
Representation Learning on Graphs: Methods and Applications. CoRR (2017)
William L. Hamilton, Kevin Clark, Jure Leskovec, Dan Jurafsky
Inducing Domain-Specific Sentiment Lexicons from Unlabeled Corpora. EMNLP (2016)
Alex Wang, William L. Hamilton, Jure Leskovec
Learning Linguistic Descriptors of User Roles in Online Communities. NLP+CSS@EMNLP (2016)
William L. Hamilton, Jure Leskovec, Dan Jurafsky
Cultural Shift or Linguistic Drift? Comparing Two Computational Measures of Semantic Change. EMNLP (2016)
William L. Hamilton, Jure Leskovec, Dan Jurafsky
Diachronic Word Embeddings Reveal Statistical Laws of Semantic Change. ACL (1) (2016)
William L. Hamilton, Kevin Clark, Jure Leskovec, Dan Jurafsky
Inducing Domain-Specific Sentiment Lexicons from Unlabeled Corpora. CoRR (2016)
William L. Hamilton, Jure Leskovec, Dan Jurafsky
Cultural Shift or Linguistic Drift? Comparing Two Computational Measures of Semantic Change. CoRR (2016)
Vinodkumar Prabhakaran, William L. Hamilton, Daniel A. McFarland, Dan Jurafsky
Predicting the Rise and Fall of Scientific Topics from Trends in their Rhetorical Framing. ACL (1) (2016)
William L. Hamilton, Jure Leskovec, Dan Jurafsky
Diachronic Word Embeddings Reveal Statistical Laws of Semantic Change. CoRR (2016)
William L. Hamilton, Mahdi Milani Fard, Joelle Pineau
Efficient learning and planning with compressed predictive states. J. Mach. Learn. Res. 15 (1) (2014)
Borja Balle, William L. Hamilton, Joelle Pineau
Methods of Moments for Learning Stochastic Languages: Unified Presentation and Empirical Comparison. ICML (2014)
William L. Hamilton, Mahdi Milani Fard, Joelle Pineau
Efficient Learning and Planning with Compressed Predictive States. CoRR (2013)
William L. Hamilton, Mahdi Milani Fard, Joelle Pineau
Modelling Sparse Dynamical Systems with Compressed Predictive State Representations. ICML (1) (2013)