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Carl Allen
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2020 – today
- 2024
- [j2]Shehzaad Zuzar Dhuliawala, Mrinmaya Sachan, Carl Allen:
Variational Classification: A Probabilistic Generalization of the Softmax Classifier. Trans. Mach. Learn. Res. 2024 (2024) - [i15]Alice Bizeul, Bernhard Schölkopf, Carl Allen:
A Probabilistic Model to explain Self-Supervised Representation Learning. CoRR abs/2402.01399 (2024) - 2023
- [i14]Shehzaad Dhuliawala, Mrinmaya Sachan, Carl Allen:
Variational Classification. CoRR abs/2305.10406 (2023) - 2022
- [c9]Yifan Hou, Wenxiang Jiao, Meizhen Liu, Carl Allen, Zhaopeng Tu, Mrinmaya Sachan:
Adapters for Enhanced Modeling of Multilingual Knowledge and Text. EMNLP (Findings) 2022: 3902-3917 - [c8]Djordje Miladinovic, Kumar Shridhar, Kushal Jain, Max B. Paulus, Joachim M. Buhmann, Carl Allen:
Learning to Drop Out: An Adversarial Approach to Training Sequence VAEs. NeurIPS 2022 - [i13]Carl Allen:
Towards a Theoretical Understanding of Word and Relation Representation. CoRR abs/2202.00486 (2022) - [i12]Ðorðe Miladinovic, Kumar Shridhar, Kushal Jain, Max B. Paulus, Joachim M. Buhmann, Carl Allen:
Learning to Drop Out: An Adversarial Approach to Training Sequence VAEs. CoRR abs/2209.12590 (2022) - [i11]Yifan Hou, Wenxiang Jiao, Meizhen Liu, Carl Allen, Zhaopeng Tu, Mrinmaya Sachan:
Adapters for Enhanced Modeling of Multilingual Knowledge and Text. CoRR abs/2210.13617 (2022) - 2021
- [j1]Benedek Rozemberczki, Carl Allen, Rik Sarkar:
Multi-Scale attributed node embedding. J. Complex Networks 9(2) (2021) - [c7]Carl Allen, Ivana Balazevic, Timothy M. Hospedales:
Interpreting Knowledge Graph Relation Representation from Word Embeddings. ICLR 2021 - 2020
- [c6]David Chang, Ivana Balazevic, Carl Allen, Daniel Chawla, Cynthia Brandt, Richard Andrew Taylor:
Benchmark and Best Practices for Biomedical Knowledge Graph Embeddings. BioNLP 2020: 167-176 - [i10]Carl Allen, Ivana Balazevic, Timothy M. Hospedales:
A Probabilistic Framework for Discriminative and Neuro-Symbolic Semi-Supervised Learning. CoRR abs/2006.05896 (2020) - [i9]David Chang, Ivana Balazevic, Carl Allen, Daniel Chawla, Cynthia Brandt, Richard Andrew Taylor:
Benchmark and Best Practices for Biomedical Knowledge Graph Embeddings. CoRR abs/2006.13774 (2020) - [i8]Ivana Balazevic, Carl Allen, Timothy M. Hospedales:
Learning the Prediction Distribution for Semi-Supervised Learning with Normalising Flows. CoRR abs/2007.02745 (2020)
2010 – 2019
- 2019
- [c5]Ivana Balazevic, Carl Allen, Timothy M. Hospedales:
TuckER: Tensor Factorization for Knowledge Graph Completion. EMNLP/IJCNLP (1) 2019: 5184-5193 - [c4]Ivana Balazevic, Carl Allen, Timothy M. Hospedales:
Hypernetwork Knowledge Graph Embeddings. ICANN (Workshop) 2019: 553-565 - [c3]Carl Allen, Timothy M. Hospedales:
Analogies Explained: Towards Understanding Word Embeddings. ICML 2019: 223-231 - [c2]Ivana Balazevic, Carl Allen, Timothy M. Hospedales:
Multi-relational Poincaré Graph Embeddings. NeurIPS 2019: 4465-4475 - [c1]Carl Allen, Ivana Balazevic, Timothy M. Hospedales:
What the Vec? Towards Probabilistically Grounded Embeddings. NeurIPS 2019: 7465-7475 - [i7]Ivana Balazevic, Carl Allen, Timothy M. Hospedales:
TuckER: Tensor Factorization for Knowledge Graph Completion. CoRR abs/1901.09590 (2019) - [i6]Carl Allen, Timothy M. Hospedales:
Analogies Explained: Towards Understanding Word Embeddings. CoRR abs/1901.09813 (2019) - [i5]Ivana Balazevic, Carl Allen, Timothy M. Hospedales:
Multi-relational Poincaré Graph Embeddings. CoRR abs/1905.09791 (2019) - [i4]Carl Allen, Ivana Balazevic, Timothy M. Hospedales:
On Understanding Knowledge Graph Representation. CoRR abs/1909.11611 (2019) - [i3]Benedek Rozemberczki, Carl Allen, Rik Sarkar:
Multi-scale Attributed Node Embedding. CoRR abs/1909.13021 (2019) - 2018
- [i2]Carl Allen, Ivana Balazevic, Timothy M. Hospedales:
What the Vec? Towards Probabilistically Grounded Embeddings. CoRR abs/1805.12164 (2018) - [i1]Ivana Balazevic, Carl Allen, Timothy M. Hospedales:
Hypernetwork Knowledge Graph Embeddings. CoRR abs/1808.07018 (2018)
Coauthor Index
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last updated on 2024-08-10 00:32 CEST by the dblp team
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