Carl Allen

Publication Activity (10 Years)

Years Active: 2018-2024
Publications (10 Years): 26

Top Topics

Graph Representation

Multi Relational Data Mining

Supervised Learning

Top Venues

J. Complex Networks

Publications

Alice Bizeul, Bernhard Schölkopf, Carl Allen
A Probabilistic Model to explain Self-Supervised Representation Learning. CoRR (2024)
Shehzaad Zuzar Dhuliawala, Mrinmaya Sachan, Carl Allen
Variational Classification: A Probabilistic Generalization of the Softmax Classifier. Trans. Mach. Learn. Res. 2024 (2024)
Shehzaad Dhuliawala, Mrinmaya Sachan, Carl Allen
Variational Classification. CoRR (2023)
Djorde 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 (2022)
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)
Yifan Hou, Wenxiang Jiao, Meizhen Liu, Carl Allen, Zhaopeng Tu, Mrinmaya Sachan
Adapters for Enhanced Modeling of Multilingual Knowledge and Text. EMNLP (Findings) (2022)
Yifan Hou, Wenxiang Jiao, Meizhen Liu, Carl Allen, Zhaopeng Tu, Mrinmaya Sachan
Adapters for Enhanced Modeling of Multilingual Knowledge and Text. CoRR (2022)
Carl Allen
Towards a Theoretical Understanding of Word and Relation Representation. CoRR (2022)
Benedek Rozemberczki, Carl Allen, Rik Sarkar
Multi-Scale attributed node embedding. J. Complex Networks 9 (2) (2021)
Carl Allen, Ivana Balazevic, Timothy M. Hospedales
Interpreting Knowledge Graph Relation Representation from Word Embeddings. ICLR (2021)
Carl Allen, Ivana Balazevic, Timothy M. Hospedales
A Probabilistic Framework for Discriminative and Neuro-Symbolic Semi-Supervised Learning. CoRR (2020)
Ivana Balazevic, Carl Allen, Timothy M. Hospedales
Learning the Prediction Distribution for Semi-Supervised Learning with Normalising Flows. CoRR (2020)
David Chang, Ivana Balazevic, Carl Allen, Daniel Chawla, Cynthia Brandt, Richard Andrew Taylor
Benchmark and Best Practices for Biomedical Knowledge Graph Embeddings. CoRR (2020)
David Chang, Ivana Balazevic, Carl Allen, Daniel Chawla, Cynthia Brandt, Richard Andrew Taylor
Benchmark and Best Practices for Biomedical Knowledge Graph Embeddings. BioNLP (2020)
Ivana Balazevic, Carl Allen, Timothy M. Hospedales
Hypernetwork Knowledge Graph Embeddings. ICANN (Workshop) (2019)
Ivana Balazevic, Carl Allen, Timothy M. Hospedales
TuckER: Tensor Factorization for Knowledge Graph Completion. CoRR (2019)
Carl Allen, Ivana Balazevic, Timothy M. Hospedales
What the Vec? Towards Probabilistically Grounded Embeddings. NeurIPS (2019)
Ivana Balazevic, Carl Allen, Timothy M. Hospedales
TuckER: Tensor Factorization for Knowledge Graph Completion. EMNLP/IJCNLP (1) (2019)
Benedek Rozemberczki, Carl Allen, Rik Sarkar
Multi-scale Attributed Node Embedding. CoRR (2019)
Carl Allen, Ivana Balazevic, Timothy M. Hospedales
On Understanding Knowledge Graph Representation. CoRR (2019)
Ivana Balazevic, Carl Allen, Timothy M. Hospedales
Multi-relational Poincaré Graph Embeddings. CoRR (2019)
Carl Allen, Timothy M. Hospedales
Analogies Explained: Towards Understanding Word Embeddings. CoRR (2019)
Carl Allen, Timothy M. Hospedales
Analogies Explained: Towards Understanding Word Embeddings. ICML (2019)
Ivana Balazevic, Carl Allen, Timothy M. Hospedales
Multi-relational Poincaré Graph Embeddings. NeurIPS (2019)
Ivana Balazevic, Carl Allen, Timothy M. Hospedales
Hypernetwork Knowledge Graph Embeddings. CoRR (2018)
Carl Allen, Ivana Balazevic, Timothy M. Hospedales
What the Vec? Towards Probabilistically Grounded Embeddings. CoRR (2018)