| Sentiment analysis: It’s complicated! K Kenyon-Dean, E Ahmed, S Fujimoto, J Georges-Filteau, C Glasz, ... Proceedings of the 2018 Conference of the North American Chapter of the …, 2018 | 96 | 2018 |
| Resolving Event Coreference with Supervised Representation Learning and Clustering-Oriented Regularization K Kenyon-Dean, JCK Cheung, D Precup Proceedings of the Seventh Joint Conference on Lexical and Computational …, 2018 | 66 | 2018 |
| Verb phrase ellipsis resolution using discriminative and margin-infused algorithms K Kenyon-Dean, JCK Cheung, D Precup Proceedings of the 2016 Conference on Empirical Methods in Natural Language …, 2016 | 25 | 2016 |
| Clustering-oriented representation learning with attractive-repulsive loss K Kenyon-Dean, A Cianflone, L Page-Caccia, G Rabusseau, ... arXiv preprint arXiv:1812.07627, 2018 | 19 | 2018 |
| Masked Autoencoders for Microscopy are Scalable Learners of Cellular Biology O Kraus, K Kenyon-Dean, S Saberian, M Fallah, P McLean, J Leung, ... Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2024 | 12 | 2024 |
| Deconstructing word embedding algorithms K Kenyon-Dean, E Newell, JCK Cheung Proceedings of the 2020 Conference on Empirical Methods in Natural Language …, 2020 | 12 | 2020 |
| Masked autoencoders are scalable learners of cellular morphology O Kraus, K Kenyon-Dean, S Saberian, M Fallah, P McLean, J Leung, ... arXiv preprint arXiv:2309.16064, 2023 | 9 | 2023 |
| Learning Efficient Task-Specific Meta-Embeddings with Word Prisms J He, KC Tsiolis, K Kenyon-Dean, JCK Cheung COLING 2020, 2020 | 9 | 2020 |
| Deconstructing and reconstructing word embedding algorithms E Newell, K Kenyon-Dean, JCK Cheung arXiv preprint arXiv:1911.13280, 2019 | 6 | 2019 |
| ViTally Consistent: Scaling Biological Representation Learning for Cell Microscopy K Kenyon-Dean, ZJ Wang, J Urbanik, K Donhauser, J Hartford, ... arXiv preprint arXiv:2411.02572, 2024 | 1 | 2024 |
| Systems and methods for generating flood hazard estimation using machine learning model and satellite data K Kenyon-dean, B Zhao, K Kasiri, Y Vahlis, T Fraser, L Morrison, ... US Patent App. 17/493,788, 2022 | 1 | 2022 |
| Word embedding algorithms as generalized low rank models and their canonical form K Kenyon-Dean McGill University (Canada), 2019 | 1 | 2019 |
| Classifying National Public Radio Transcribed Interviews J Kabbara, K Kenyon-Dean, W Zhang | 1 | 2015 |
| Benchmarking Transcriptomics Foundation Models for Perturbation Analysis: one PCA still rules them all I Bendidi, S Whitfield, K Kenyon-Dean, HB Yedder, YE Mesbahi, ... arXiv preprint arXiv:2410.13956, 2024 | | 2024 |
| Utilizing masked autoencoder generative models to extract microscopy representation autoencoder embeddings OZ Kraus, KR Kenyon-Dean, M Saberian, M Fallah, PF McLean, ... US Patent 12,119,090, 2024 | | 2024 |
| Utilizing masked autoencoder generative models to extract microscopy representation autoencoder embeddings OZ Kraus, KR Kenyon-Dean, M Saberian, M Fallah, PF McLean, ... US Patent 12,119,091, 2024 | | 2024 |
| Systems and methods for generating visual representations of climate hazard risks K Kenyon-dean, M Torrance US Patent App. 17/959,143, 2023 | | 2023 |
| Trouble in Gaussian City: When Laser-Tanks use Potential Fields K Kenyon-Dean, C Verbrugge | | 2017 |
| Towards scientific discovery with dictionary learning: Extracting biological concepts from microscopy foundation models K Donhauser, GE Moran, A Ravuri, K Kenyon-Dean, K Ulicna, ... Interpretable AI: Past, Present and Future, 0 | | |
Jackie Chi Kit CheungMcGill UniversityVerified email at cs.mcgill.ca
