Carl Allen

According to our database, Carl Allen authored at least 18 papers between 2019 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Variational Classification: A Probabilistic Generalization of the Softmax Classifier.

Shehzaad Zuzar Dhuliawala, Mrinmaya Sachan, Carl Allen

Trans. Mach. Learn. Res., 2024

Unpicking Data at the Seams: VAEs, Disentanglement and Independent Components.

Carl Allen

CoRR, 2024

A Probabilistic Model to explain Self-Supervised Representation Learning.

Alice Bizeul, Bernhard Schölkopf, Carl Allen

CoRR, 2024

2023

Variational Classification.

Shehzaad Dhuliawala, Mrinmaya Sachan, Carl Allen

CoRR, 2023

2022

Towards a Theoretical Understanding of Word and Relation Representation.

Carl Allen

CoRR, 2022

Learning to Drop Out: An Adversarial Approach to Training Sequence VAEs.

Djordje Miladinovic, Kumar Shridhar, Kushal Jain, Max B. Paulus, Joachim M. Buhmann, Carl Allen

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Adapters for Enhanced Modeling of Multilingual Knowledge and Text.

Yifan Hou, Wenxiang Jiao, Meizhen Liu, Carl Allen, Zhaopeng Tu, Mrinmaya Sachan

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2022, 2022

2021

Multi-Scale attributed node embedding.

Benedek Rozemberczki, Carl Allen, Rik Sarkar

J. Complex Networks, 2021

Interpreting Knowledge Graph Relation Representation from Word Embeddings.

Carl Allen, Ivana Balazevic, Timothy M. Hospedales

Proceedings of the 9th International Conference on Learning Representations, 2021

2020

Learning the Prediction Distribution for Semi-Supervised Learning with Normalising Flows.

Ivana Balazevic, Carl Allen, Timothy M. Hospedales

CoRR, 2020

A Probabilistic Framework for Discriminative and Neuro-Symbolic Semi-Supervised Learning.

Carl Allen, Ivana Balazevic, Timothy M. Hospedales

CoRR, 2020

Benchmark and Best Practices for Biomedical Knowledge Graph Embeddings.

David Chang, Ivana Balazevic, Carl Allen, Daniel Chawla, Cynthia Brandt, Richard Andrew Taylor

Proceedings of the 19th SIGBioMed Workshop on Biomedical Language Processing, 2020

2019

On Understanding Knowledge Graph Representation.

Carl Allen, Ivana Balazevic, Timothy M. Hospedales

CoRR, 2019

Multi-relational Poincaré Graph Embeddings.

Ivana Balazevic, Carl Allen, Timothy M. Hospedales

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

What the Vec? Towards Probabilistically Grounded Embeddings.

Carl Allen, Ivana Balazevic, Timothy M. Hospedales

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Analogies Explained: Towards Understanding Word Embeddings.

Carl Allen, Timothy M. Hospedales

Proceedings of the 36th International Conference on Machine Learning, 2019

Hypernetwork Knowledge Graph Embeddings.

Ivana Balazevic, Carl Allen, Timothy M. Hospedales

Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2019 - 28th International Conference on Artificial Neural Networks, Munich, Germany, September 17-19, 2019, Proceedings, 2019

TuckER: Tensor Factorization for Knowledge Graph Completion.

Ivana Balazevic, Carl Allen, Timothy M. Hospedales

Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing, 2019