Ivana Balažević
I am a Research Scientist at Google DeepMind.
I obtained my PhD from The University of Edinburgh, where I was supervised by Tim Hospedales and Ivan Titov. The focus of my PhD was on learning representations of entities and relations from knowledge graph data. During my PhD, I interned at the Samsung AI Center Cambridge and at Facebook AI Research (FAIR) with Sebastian Riedel. I hold a BSc in Computer Science from the Faculty of Electrical Engineering and Computing, University of Zagreb, an MSc in Computer Science from the Technische Universität Berlin and an MSc in Data Science from the University of Edinburgh.
Publications
Memory Consolidation Enables Long-Context Video Understanding
Ivana Balažević*, Yuge Shi*, Pinelopi Papalampidi*, Rahma Chaabouni, Skanda Koppula, Olivier Hénaff
arXiv:2402.05861, 2024
[paper]
Towards In-context Scene Understanding
Ivana Balažević*, David Steiner*, Nikhil Parthasarathy, Relja Arandjelović, Olivier Hénaff
NeurIPS, 2023 (Spotlight)
[paper]
Cutting Down on Prompts and Parameters: Simple Few-Shot Learning with Language Models
Robert L. Logan IV, Ivana Balažević, Eric Wallace, Fabio Petroni, Sameer Singh, Sebastian Riedel Findings of ACL, 2022
[paper] [code]
Interpreting Knowledge Graph Relation Representation from Word Embeddings
Carl Allen*, Ivana Balažević*, Timothy Hospedales, ICLR, 2021
[paper]
Multi-relational Poincaré Graph Embeddings
Ivana Balažević, Carl Allen, Timothy Hospedales, NeurIPS, 2019
[paper] [code]
What the Vec? Towards Probabilistically Grounded Embeddings
Carl Allen, Ivana Balažević, Timothy Hospedales, NeurIPS, 2019
[paper]
TuckER: Tensor Factorization for Knowledge Graph Completion
Ivana Balažević, Carl Allen, Timothy Hospedales, EMNLP, 2019 (Oral)
[paper] [code] [slides][video]
Hypernetwork Knowledge Graph Embeddings
Ivana Balažević, Carl Allen, Timothy Hospedales, ICANN, 2019 (Oral)
[paper] [code] [slides]
Preprints
Learning the Prediction Distribution for Semi-Supervised Learning with Normalising Flows
Ivana Balažević*, Carl Allen*, Timothy Hospedales, arXiv:2007.02745, 2020
[paper] [code]
A Probabilistic Framework for Discriminative and Neuro-Symbolic Semi-Supervised Learning
Carl Allen, Ivana Balažević, Timothy Hospedales, arXiv:2006.05896, 2020
[paper]
Workshops
Cutting Down on Prompts and Parameters: Simple Few-Shot Learning with Language Models
Robert L. Logan IV, Ivana Balažević, Eric Wallace, Fabio Petroni, Sameer Singh, Sebastian Riedel NeurIPS ENLSP Workshop, 2021 (Best Poster)
[paper] [code]
Benchmark and Best Practices for Biomedical Knowledge Graph Embeddings
David Chang, Ivana Balažević, Carl Allen, Daniel Chawla, Cynthia Brandt, Andrew Taylor
ACL BioNLP Workshop, 2020
[paper]
TuckER: Tensor Factorization for Knowledge Graph Completion
Ivana Balažević, Carl Allen, Timothy Hospedales, ICML AMTL Workshop, 2019
[paper]
Links
Contact
Email: balazevic@google.com