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ORCIDWilliam L. Hamilton
Person information
- affiliation: Mila - Quebec AI Institute, Montréal, QC, Canada
- affiliation: McGill University, Montréal, QC, Canada
- affiliation (former): Stanford University, Stanford, CA, USA
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2020 – today
- 2024
[i51]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 abs/2405.01616 (2024)- 2023
- [j7]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): 425-445 (2023) - 2022
- [j6]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) - [j5]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): 970-976 (2022) - [j4]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): 1458-1459 (2022) - [c42]Mikhail Galkin, Etienne G. Denis, Jiapeng Wu, William L. Hamilton:
NodePiece: Compositional and Parameter-Efficient Representations of Large Knowledge Graphs. ICLR 2022 - [c41]Andjela Mladenovic, Avishek Joey Bose, Hugo Berard, William L. Hamilton, Simon Lacoste-Julien, Pascal Vincent, Gauthier Gidel:
Online Adversarial Attacks. ICLR 2022 - 2021
- [c40]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: 6648-6662 - [c39]Agnieszka Slowik, Abhinav Gupta, William L. Hamilton, Mateja Jamnik, Sean B. Holden, Chris Pal:
Structural Inductive Biases in Emergent Communication. CogSci 2021 - [c38]Devendra Singh Sachan, Yuhao Zhang, Peng Qi, William L. Hamilton:
Do Syntax Trees Help Pre-trained Transformers Extract Information? EACL 2021: 2647-2661 - [c37]Dora Jambor, Komal K. Teru, Joelle Pineau, William L. Hamilton:
Exploring the Limits of Few-Shot Link Prediction in Knowledge Graphs. EACL 2021: 2816-2822 - [c36]Dylan Sandfelder, Priyesh Vijayan, William L. Hamilton:
Ego-GNNs: Exploiting Ego Structures in Graph Neural Networks. ICASSP 2021: 8523-8527 - [c35]Lu Liu, William L. Hamilton, Guodong Long, Jing Jiang, Hugo Larochelle:
A Universal Representation Transformer Layer for Few-Shot Image Classification. ICLR 2021 - [c34]Zichao Yan, William L. Hamilton, Mathieu Blanchette:
Neural representation and generation for RNA secondary structures. ICLR 2021 - [c33]Dominique Beaini, Saro Passaro, Vincent Létourneau, William L. Hamilton, Gabriele Corso, Pietro Lió:
Directional Graph Networks. ICML 2021: 748-758 - [c32]Devin Kreuzer, Dominique Beaini, William L. Hamilton, Vincent Létourneau, Prudencio Tossou:
Rethinking Graph Transformers with Spectral Attention. NeurIPS 2021: 21618-21629 - [c31]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: 25968-25981 - [i50]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 abs/2101.00408 (2021) - [i49]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 abs/2101.10249 (2021) - [i48]Zichao Yan, William L. Hamilton, Mathieu Blanchette:
Neural representation and generation for RNA secondary structures. CoRR abs/2102.00925 (2021) - [i47]Dora Jambor, Komal K. Teru, Joelle Pineau, William L. Hamilton:
Exploring the Limits of Few-Shot Link Prediction in Knowledge Graphs. CoRR abs/2102.03419 (2021) - [i46]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 abs/2102.10062 (2021) - [i45]Andjela Mladenovic, Avishek Joey Bose, Hugo Berard, William L. Hamilton, Simon Lacoste-Julien, Pascal Vincent, Gauthier Gidel:
Online Adversarial Attacks. CoRR abs/2103.02014 (2021) - [i44]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 abs/2105.10488 (2021) - [i43]Devin Kreuzer, Dominique Beaini, William L. Hamilton, Vincent Létourneau, Prudencio Tossou:
Rethinking Graph Transformers with Spectral Attention. CoRR abs/2106.03893 (2021) - [i42]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 abs/2106.05346 (2021) - [i41]Mikhail Galkin, Jiapeng Wu, Etienne G. Denis, William L. Hamilton:
NodePiece: Compositional and Parameter-Efficient Representations of Large Knowledge Graphs. CoRR abs/2106.12144 (2021) - [i40]Dylan Sandfelder, Priyesh Vijayan, William L. Hamilton:
Ego-GNNs: Exploiting Ego Structures in Graph Neural Networks. CoRR abs/2107.10957 (2021) - [i39]Vincent Mallet, Carlos G. Oliver, William L. Hamilton:
Edge-similarity-aware Graph Neural Networks. CoRR abs/2109.09432 (2021) - 2020
- [b2]William L. Hamilton:
Graph Representation Learning. Synthesis Lectures on Artificial Intelligence and Machine Learning, Morgan & Claypool Publishers 2020, ISBN 978-3-031-00460-5 - [j3]Zichao Yan, William L. Hamilton, Mathieu Blanchette:
Graph neural representational learning of RNA secondary structures for predicting RNA-protein interactions. Bioinform. 36(Supplement-1): i276-i284 (2020) - [c30]Koustuv Sinha, Prasanna Parthasarathi, Jasmine Wang, Ryan Lowe, William L. Hamilton, Joelle Pineau:
Learning an Unreferenced Metric for Online Dialogue Evaluation. ACL 2020: 2430-2441 - [c29]Jiapeng Wu, Meng Cao, Jackie Chi Kit Cheung, William L. Hamilton:
TeMP: Temporal Message Passing for Temporal Knowledge Graph Completion. EMNLP (1) 2020: 5730-5746 - [c28]Kian Ahrabian, Aarash Feizi, Yasmin Salehi, William L. Hamilton, Avishek Joey Bose:
Structure Aware Negative Sampling in Knowledge Graphs. EMNLP (1) 2020: 6093-6101 - [c27]Jin Dong, Marc-Antoine Rondeau, William L. Hamilton:
Distilling Structured Knowledge for Text-Based Relational Reasoning. EMNLP (1) 2020: 6782-6791 - [c26]Avishek Joey Bose, Ariella Smofsky, Renjie Liao, Prakash Panangaden, William L. Hamilton:
Latent Variable Modelling with Hyperbolic Normalizing Flows. ICML 2020: 1045-1055 - [c25]Komal K. Teru, Etienne G. Denis, William L. Hamilton:
Inductive Relation Prediction by Subgraph Reasoning. ICML 2020: 9448-9457 - [c24]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 - [c23]Avishek Joey Bose, Gauthier Gidel, Hugo Berard, Andre Cianflone, Pascal Vincent, Simon Lacoste-Julien, William L. Hamilton:
Adversarial Example Games. NeurIPS 2020 - [c22]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: 72-77 - [i38]Agnieszka Slowik, Abhinav Gupta, William L. Hamilton, Mateja Jamnik, Sean B. Holden:
Towards Graph Representation Learning in Emergent Communication. CoRR abs/2001.09063 (2020) - [i37]Agnieszka Slowik, Abhinav Gupta, William L. Hamilton, Mateja Jamnik, Sean B. Holden, Christopher J. Pal:
Exploring Structural Inductive Biases in Emergent Communication. CoRR abs/2002.01335 (2020) - [i36]Avishek Joey Bose, Ariella Smofsky, Renjie Liao, Prakash Panangaden, William L. Hamilton:
Latent Variable Modelling with Hyperbolic Normalizing Flows. CoRR abs/2002.06336 (2020) - [i35]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 abs/2002.09127 (2020) - [i34]Koustuv Sinha, Shagun Sodhani, Joelle Pineau, William L. Hamilton:
Evaluating Logical Generalization in Graph Neural Networks. CoRR abs/2003.06560 (2020) - [i33]Koustuv Sinha, Prasanna Parthasarathi, Jasmine Wang, Ryan Lowe, William L. Hamilton, Joelle Pineau:
Learning an Unreferenced Metric for Online Dialogue Evaluation. CoRR abs/2005.00583 (2020) - [i32]Lu Liu, William L. Hamilton, Guodong Long, Jing Jiang, Hugo Larochelle:
A Universal Representation Transformer Layer for Few-Shot Image Classification. CoRR abs/2006.11702 (2020) - [i31]Avishek Joey Bose, Gauthier Gidel, Hugo Berard, Andre Cianflone, Pascal Vincent, Simon Lacoste-Julien, William L. Hamilton:
Adversarial Example Games. CoRR abs/2007.00720 (2020) - [i30]Devendra Singh Sachan, Yuhao Zhang, Peng Qi, William L. Hamilton:
Do Syntax Trees Help Pre-trained Transformers Extract Information? CoRR abs/2008.09084 (2020) - [i29]Carlos G. Oliver, Vincent Mallet, Pericles Philippopoulos, William L. Hamilton, Jérôme Waldispühl:
VeRNAl: A Tool for Mining Fuzzy Network Motifs in RNA. CoRR abs/2009.00664 (2020) - [i28]Kian Ahrabian, Aarash Feizi, Yasmin Salehi, William L. Hamilton, Avishek Joey Bose:
Structure Aware Negative Sampling in Knowledge Graphs. CoRR abs/2009.11355 (2020) - [i27]Dominique Beaini, Saro Passaro, Vincent Létourneau, William L. Hamilton, Gabriele Corso, Pietro Liò:
Directional Graph Networks. CoRR abs/2010.02863 (2020) - [i26]Jiapeng Wu, Meng Cao, Jackie Chi Kit Cheung, William L. Hamilton:
TeMP: Temporal Message Passing for Temporal Knowledge Graph Completion. CoRR abs/2010.03526 (2020) - [i25]Devendra Singh Sachan, Lingfei Wu, Mrinmaya Sachan, William L. Hamilton:
Stronger Transformers for Neural Multi-Hop Question Generation. CoRR abs/2010.11374 (2020)
2010 – 2019
- 2019
- [c21]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: 4602-4609 - [c20]Koustuv Sinha, Shagun Sodhani, Jin Dong, Joelle Pineau, William L. Hamilton:
CLUTRR: A Diagnostic Benchmark for Inductive Reasoning from Text. EMNLP/IJCNLP (1) 2019: 4505-4514 - [c19]Petar Velickovic, William Fedus, William L. Hamilton, Pietro Liò, Yoshua Bengio, R. Devon Hjelm:
Deep Graph Infomax. ICLR (Poster) 2019 - [c18]Avishek Joey Bose, William L. Hamilton:
Compositional Fairness Constraints for Graph Embeddings. ICML 2019: 715-724 - [c17]Charles C. Onu, Jonathan Lebensold, William L. Hamilton, Doina Precup:
Neural Transfer Learning for Cry-Based Diagnosis of Perinatal Asphyxia. INTERSPEECH 2019: 3053-3057 - [c16]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: 4257-4267 - [i24]Avishek Joey Bose, William L. Hamilton:
Compositional Fairness Constraints for Graph Embeddings. CoRR abs/1905.10674 (2019) - [i23]Avishek Joey Bose, Andre Cianflone, William L. Hamilton:
Generalizable Adversarial Attacks Using Generative Models. CoRR abs/1905.10864 (2019) - [i22]Charles C. Onu, Jonathan Lebensold, William L. Hamilton, Doina Precup:
Neural Transfer Learning for Cry-based Diagnosis of Perinatal Asphyxia. CoRR abs/1906.10199 (2019) - [i21]Koustuv Sinha, Shagun Sodhani, Jin Dong, Joelle Pineau, William L. Hamilton:
CLUTRR: A Diagnostic Benchmark for Inductive Reasoning from Text. CoRR abs/1908.06177 (2019) - [i20]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 abs/1910.00760 (2019) - [i19]Jonathan Lebensold, William L. Hamilton, Borja Balle, Doina Precup:
Actor Critic with Differentially Private Critic. CoRR abs/1910.05876 (2019) - [i18]Komal K. Teru, William L. Hamilton:
Inductive Relation Prediction on Knowledge Graphs. CoRR abs/1911.06962 (2019) - [i17]Avishek Joey Bose, Ankit Jain, Piero Molino, William L. Hamilton:
Meta-Graph: Few shot Link Prediction via Meta Learning. CoRR abs/1912.09867 (2019) - 2018
- [b1]William L. Hamilton:
Representation learning methods for computational social science. Stanford University, USA, 2018 - [c15]Jiaxuan You, Rex Ying, Xiang Ren, William L. Hamilton, Jure Leskovec:
GraphRNN: Generating Realistic Graphs with Deep Auto-regressive Models. ICML 2018: 5694-5703 - [c14]Rex Ying, Ruining He, Kaifeng Chen, Pong Eksombatchai, William L. Hamilton, Jure Leskovec:
Graph Convolutional Neural Networks for Web-Scale Recommender Systems. KDD 2018: 974-983 - [c13]William L. Hamilton, Payal Bajaj, Marinka Zitnik, Dan Jurafsky, Jure Leskovec:
Embedding Logical Queries on Knowledge Graphs. NeurIPS 2018: 2030-2041 - [c12]Zhitao Ying, Jiaxuan You, Christopher Morris, Xiang Ren, William L. Hamilton, Jure Leskovec:
Hierarchical Graph Representation Learning with Differentiable Pooling. NeurIPS 2018: 4805-4815 - [c11]Srijan Kumar, William L. Hamilton, Jure Leskovec, Dan Jurafsky:
Community Interaction and Conflict on the Web. WWW 2018: 933-943 - [i16]Jiaxuan You, Rex Ying, Xiang Ren, William L. Hamilton, Jure Leskovec:
GraphRNN: A Deep Generative Model for Graphs. CoRR abs/1802.08773 (2018) - [i15]Srijan Kumar, William L. Hamilton, Jure Leskovec, Dan Jurafsky:
Community Interaction and Conflict on the Web. CoRR abs/1803.03697 (2018) - [i14]William L. Hamilton, Payal Bajaj, Marinka Zitnik, Dan Jurafsky, Jure Leskovec:
Querying Complex Networks in Vector Space. CoRR abs/1806.01445 (2018) - [i13]Rex Ying, Ruining He, Kaifeng Chen, Pong Eksombatchai, William L. Hamilton, Jure Leskovec:
Graph Convolutional Neural Networks for Web-Scale Recommender Systems. CoRR abs/1806.01973 (2018) - [i12]Rex Ying, Jiaxuan You, Christopher Morris, Xiang Ren, William L. Hamilton, Jure Leskovec:
Hierarchical Graph Representation Learning with Differentiable Pooling. CoRR abs/1806.08804 (2018) - [i11]Petar Velickovic, William Fedus, William L. Hamilton, Pietro Liò, Yoshua Bengio, R. Devon Hjelm:
Deep Graph Infomax. CoRR abs/1809.10341 (2018) - [i10]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 abs/1810.02244 (2018) - [i9]Koustuv Sinha, Shagun Sodhani, William L. Hamilton, Joelle Pineau:
Compositional Language Understanding with Text-based Relational Reasoning. CoRR abs/1811.02959 (2018) - 2017
- [j2]William L. Hamilton, Rex Ying, Jure Leskovec:
Representation Learning on Graphs: Methods and Applications. IEEE Data Eng. Bull. 40(3): 52-74 (2017) - [c10]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: 377-386 - [c9]William L. Hamilton, Justine Zhang, Cristian Danescu-Niculescu-Mizil, Dan Jurafsky, Jure Leskovec:
Loyalty in Online Communities. ICWSM 2017: 540-543 - [c8]William L. Hamilton, Zhitao Ying, Jure Leskovec:
Inductive Representation Learning on Large Graphs. NIPS 2017: 1024-1034 - [i8]William L. Hamilton, Justine Zhang, Cristian Danescu-Niculescu-Mizil, Dan Jurafsky, Jure Leskovec:
Loyalty in Online Communities. CoRR abs/1703.03386 (2017) - [i7]Justine Zhang, William L. Hamilton, Cristian Danescu-Niculescu-Mizil, Dan Jurafsky, Jure Leskovec:
Community Identity and User Engagement in a Multi-Community Landscape. CoRR abs/1705.09665 (2017) - [i6]William L. Hamilton, Rex Ying, Jure Leskovec:
Inductive Representation Learning on Large Graphs. CoRR abs/1706.02216 (2017) - [i5]William L. Hamilton, Rex Ying, Jure Leskovec:
Representation Learning on Graphs: Methods and Applications. CoRR abs/1709.05584 (2017) - 2016
- [c7]William L. Hamilton, Jure Leskovec, Dan Jurafsky:
Diachronic Word Embeddings Reveal Statistical Laws of Semantic Change. ACL (1) 2016 - [c6]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 - [c5]Alex Wang, William L. Hamilton, Jure Leskovec:
Learning Linguistic Descriptors of User Roles in Online Communities. NLP+CSS@EMNLP 2016: 76-85 - [c4]William L. Hamilton, Kevin Clark, Jure Leskovec, Dan Jurafsky:
Inducing Domain-Specific Sentiment Lexicons from Unlabeled Corpora. EMNLP 2016: 595-605 - [c3]William L. Hamilton, Jure Leskovec, Dan Jurafsky:
Cultural Shift or Linguistic Drift? Comparing Two Computational Measures of Semantic Change. EMNLP 2016: 2116-2121 - [i4]William L. Hamilton, Jure Leskovec, Dan Jurafsky:
Diachronic Word Embeddings Reveal Statistical Laws of Semantic Change. CoRR abs/1605.09096 (2016) - [i3]William L. Hamilton, Kevin Clark, Jure Leskovec, Dan Jurafsky:
Inducing Domain-Specific Sentiment Lexicons from Unlabeled Corpora. CoRR abs/1606.02820 (2016) - [i2]William L. Hamilton, Jure Leskovec, Dan Jurafsky:
Cultural Shift or Linguistic Drift? Comparing Two Computational Measures of Semantic Change. CoRR abs/1606.02821 (2016) - 2014
- [j1]William L. Hamilton, Mahdi Milani Fard, Joelle Pineau:
Efficient learning and planning with compressed predictive states. J. Mach. Learn. Res. 15(1): 3395-3439 (2014) - [c2]Borja Balle, William L. Hamilton, Joelle Pineau:
Methods of Moments for Learning Stochastic Languages: Unified Presentation and Empirical Comparison. ICML 2014: 1386-1394 - 2013
- [c1]William L. Hamilton, Mahdi Milani Fard, Joelle Pineau:
Modelling Sparse Dynamical Systems with Compressed Predictive State Representations. ICML (1) 2013: 178-186 - [i1]William L. Hamilton, Mahdi Milani Fard, Joelle Pineau:
Efficient Learning and Planning with Compressed Predictive States. CoRR abs/1312.0286 (2013)
Coauthor Index
Daniel Jurafsky
aka: Dan Jurafsky
aka: Dan Jurafsky
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