Carl Allen

28 papers A* 5Journal 19Unranked 4
YearRankTypeTitle / Venue / Authors
2024 J jnl
A Probabilistic Model behind Self- Supervised Learning.
Trans. Mach. Learn. Res.
Alice Bizeul, Bernhard Schölkopf, Carl Allen
2024 J jnl
A Probabilistic Model to explain Self-Supervised Representation Learning.
CoRR
Alice Bizeul, Bernhard Schölkopf, Carl Allen
2024 J jnl
Unpicking Data at the Seams: VAEs, Disentanglement and Independent Components.
CoRR
Carl Allen
2024 J jnl
Variational Classification: A Probabilistic Generalization of the Softmax Classifier.
Trans. Mach. Learn. Res.
Shehzaad Zuzar Dhuliawala, Mrinmaya Sachan, Carl Allen
2023 J jnl
Variational Classification.
CoRR
Shehzaad Dhuliawala, Mrinmaya Sachan, Carl Allen
2022 — conf
Adapters for Enhanced Modeling of Multilingual Knowledge and Text.
EMNLP (Findings)
Yifan Hou, Wenxiang Jiao, Meizhen Liu, Carl Allen, Zhaopeng Tu, Mrinmaya Sachan
2022 J jnl
Adapters for Enhanced Modeling of Multilingual Knowledge and Text.
CoRR
Yifan Hou, Wenxiang Jiao, Meizhen Liu, Carl Allen, Zhaopeng Tu, Mrinmaya Sachan
2022 A* conf
Learning to Drop Out: An Adversarial Approach to Training Sequence VAEs.
NeurIPS
Djordje Miladinovic, Kumar Shridhar, Kushal Jain, Max B. Paulus, Joachim M. Buhmann, Carl Allen
2022 J jnl
Learning to Drop Out: An Adversarial Approach to Training Sequence VAEs.
CoRR
Ðorðe Miladinovic, Kumar Shridhar, Kushal Jain, Max B. Paulus, Joachim M. Buhmann, Carl Allen
2022 J jnl
Towards a Theoretical Understanding of Word and Relation Representation.
CoRR
Carl Allen
2021 A* conf
Interpreting Knowledge Graph Relation Representation from Word Embeddings.
ICLR
Carl Allen, Ivana Balazevic, Timothy M. Hospedales
2021 J jnl
Multi-Scale attributed node embedding.
J. Complex Networks
Benedek Rozemberczki, Carl Allen, Rik Sarkar
2020 J jnl
A Probabilistic Framework for Discriminative and Neuro-Symbolic Semi-Supervised Learning.
CoRR
Carl Allen, Ivana Balazevic, Timothy M. Hospedales
2020 — conf
Benchmark and Best Practices for Biomedical Knowledge Graph Embeddings.
BioNLP
David Chang, Ivana Balazevic, Carl Allen, Daniel Chawla, Cynthia Brandt, Richard Andrew Taylor
2020 J jnl
Benchmark and Best Practices for Biomedical Knowledge Graph Embeddings.
CoRR
David Chang, Ivana Balazevic, Carl Allen, Daniel Chawla, Cynthia Brandt, Richard Andrew Taylor
2020 J jnl
Learning the Prediction Distribution for Semi-Supervised Learning with Normalising Flows.
CoRR
Ivana Balazevic, Carl Allen, Timothy M. Hospedales
2019 A* conf
Analogies Explained: Towards Understanding Word Embeddings.
ICML
Carl Allen, Timothy M. Hospedales
2019 J jnl
Analogies Explained: Towards Understanding Word Embeddings.
CoRR
Carl Allen, Timothy M. Hospedales
2019 — conf
Hypernetwork Knowledge Graph Embeddings.
ICANN (Workshop)
Ivana Balazevic, Carl Allen, Timothy M. Hospedales
2019 A* conf
Multi-relational Poincaré Graph Embeddings.
NeurIPS
Ivana Balazevic, Carl Allen, Timothy M. Hospedales
2019 J jnl
Multi-relational Poincaré Graph Embeddings.
CoRR
Ivana Balazevic, Carl Allen, Timothy M. Hospedales
2019 J jnl
Multi-scale Attributed Node Embedding.
CoRR
Benedek Rozemberczki, Carl Allen, Rik Sarkar
2019 J jnl
On Understanding Knowledge Graph Representation.
CoRR
Carl Allen, Ivana Balazevic, Timothy M. Hospedales
2019 — conf
TuckER: Tensor Factorization for Knowledge Graph Completion.
EMNLP/IJCNLP (1)
Ivana Balazevic, Carl Allen, Timothy M. Hospedales
2019 J jnl
TuckER: Tensor Factorization for Knowledge Graph Completion.
CoRR
Ivana Balazevic, Carl Allen, Timothy M. Hospedales
2019 A* conf
What the Vec? Towards Probabilistically Grounded Embeddings.
NeurIPS
Carl Allen, Ivana Balazevic, Timothy M. Hospedales
2018 J jnl
Hypernetwork Knowledge Graph Embeddings.
CoRR
Ivana Balazevic, Carl Allen, Timothy M. Hospedales
2018 J jnl
What the Vec? Towards Probabilistically Grounded Embeddings.
CoRR
Carl Allen, Ivana Balazevic, Timothy M. Hospedales