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Michael Boratko
Michael Boratko
Research Scientist, Google
Dirección de correo verificada de google.com - Página principal
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Smoothing the Geometry of Probabilistic Box Embeddings
X Li, L Vilnis, D Zhang, M Boratko, A McCallum
International Conference on Learning Representations, 2019
872019
Modeling Fine-Grained Entity Types with Box Embeddings
Y Onoe, M Boratko, G Durrett
arXiv preprint arXiv:2101.00345, 2021
652021
A Systematic Classification of Knowledge, Reasoning, and Context within the ARC Dataset
M Boratko, H Padigela, D Mikkilineni, P Yuvraj, R Das, A McCallum, ...
Proceedings of the Workshop on Machine Reading for Question Answering …, 2018
592018
ProtoQA: A Question Answering Dataset for Prototypical Common-Sense Reasoning
M Boratko, XL Li, R Das, T O'Gorman, D Le, A McCallum
Proceedings of the 2020 Conference on Empirical Methods in Natural Language …, 2020
492020
Improving Local Identifiability in Probabilistic Box Embeddings
SS Dasgupta, M Boratko, D Zhang, L Vilnis, XL Li, A McCallum
Advances in Neural Information Processing Systems, 2020
422020
Probabilistic box embeddings for uncertain knowledge graph reasoning
X Chen, M Boratko, M Chen, SS Dasgupta, XL Li, A McCallum
arXiv preprint arXiv:2104.04597, 2021
332021
Modeling label space interactions in multi-label classification using box embeddings
D Patel, P Dangati, JY Lee, M Boratko, A McCallum
ICLR 2022 Poster, 2022
262022
Representing Joint Hierarchies with Box Embeddings
D Patel, SS Dasgupta, M Boratko, XL Li, L Vilnis, A McCallum
Automated Knowledge Base Construction, 2020
182020
Word2box: Capturing set-theoretic semantics of words using box embeddings
SS Dasgupta, M Boratko, S Mishra, S Atmakuri, D Patel, XL Li, ...
arXiv preprint arXiv:2106.14361, 2021
12*2021
Capacity and bias of learned geometric embeddings for directed graphs
M Boratko, D Zhang, N Monath, L Vilnis, KL Clarkson, A McCallum
Advances in Neural Information Processing Systems 34, 16423-16436, 2021
112021
Box embeddings: An open-source library for representation learning using geometric structures
T Chheda, P Goyal, T Tran, D Patel, M Boratko, SS Dasgupta, ...
arXiv preprint arXiv:2109.04997, 2021
82021
Box-to-box transformations for modeling joint hierarchies
SS Dasgupta, XL Li, M Boratko, D Zhang, A McCallum
Proceedings of the 6th Workshop on Representation Learning for NLP (RepL4NLP …, 2021
62021
An Interface for Annotating Science Questions
M Boratko, H Padigela, D Mikkilineni, P Yuvraj, R Das, A McCallum, ...
Proceedings of the 2018 Conference on Empirical Methods in Natural Language …, 2018
62018
Modeling transitivity and cyclicity in directed graphs via binary code box embeddings
D Zhang, M Boratko, C Musco, A McCallum
Advances in Neural Information Processing Systems 35, 10587-10599, 2022
42022
Min/Max Stability and Box Distributions
M Boratko, J Burroni, SS Dasgupta, A McCallum
Uncertainty in Artificial Intelligence, 2021
42021
An evaluative measure of clustering methods incorporating hyperparameter sensitivity
S Mishra, N Monath, M Boratko, A Kobren, A McCallum
Proceedings of the AAAI Conference on Artificial Intelligence 36 (7), 7788-7796, 2022
22022
Gecko: Versatile Text Embeddings Distilled from Large Language Models
J Lee, Z Dai, X Ren, B Chen, D Cer, JR Cole, K Hui, M Boratko, ...
arXiv preprint arXiv:2403.20327, 2024
2024
MEASURE-THEORETIC SET REPRESENTATION LEARNING
M Boratko, D Patel, SS Dasgupta, A McCallum
2022
On the Growth of Sobolev Norms for the Nonlinear Schrödinger Equation on Tori and Boundary Unique Continuation for Elliptic PDE
M Boratko
2018
El sistema no puede realizar la operación en estos momentos. Inténtalo de nuevo más tarde.
Artículos 1–19