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06/02/2023
Towards In-context Scene Understanding
In-context learningx2013the ability to configure a model's behavior with...
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01/31/2022
Learning Representations of Entities and Relations
Encoding facts as representations of entities and binary relationships b...
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06/24/2021
Cutting Down on Prompts and Parameters: Simple Few-Shot Learning with Language Models
Prompting language models (LMs) with training examples and task descript...
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07/06/2020
Learning the Prediction Distribution for Semi-Supervised Learning with Normalising Flows
As data volumes continue to grow, the labelling process increasingly bec...
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06/24/2020
Benchmark and Best Practices for Biomedical Knowledge Graph Embeddings
Much of biomedical and healthcare data is encoded in discrete, symbolic ...
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06/10/2020
A Probabilistic Framework for Discriminative and Neuro-Symbolic Semi-Supervised Learning
In semi-supervised learning (SSL), a rule to predict labels y for data x...
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09/25/2019
On Understanding Knowledge Graph Representation
Many methods have been developed to represent knowledge graph data, whic...
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05/23/2019
Multi-relational Poincaré Graph Embeddings
Hyperbolic embeddings have recently gained attention in machine learning...
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01/28/2019
TuckER: Tensor Factorization for Knowledge Graph Completion
Knowledge graphs are structured representations of real world facts. How...
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08/21/2018
Hypernetwork Knowledge Graph Embeddings
Knowledge graphs are large graph-structured databases of facts, which ty...
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05/30/2018
What the Vec? Towards Probabilistically Grounded Embeddings
Vector representation, or embedding, of words is commonly achieved with ...
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08/30/2016