Jovana Mitrovic

According to our database, Jovana Mitrovic authored at least 18 papers between 2016 and 2024.

Collaborative distances:

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

2024

Synth²: Boosting Visual-Language Models with Synthetic Captions and Image Embeddings.

Sahand Sharifzadeh, Christos Kaplanis, Shreya Pathak, Dharshan Kumaran, Anastasija Ilic, Jovana Mitrovic, Charles Blundell, Andrea Banino

CoRR, 2024

Improving fine-grained understanding in image-text pre-training.

Ioana Bica, Anastasija Ilic, Matthias Bauer, Goker Erdogan, Matko Bosnjak, Christos Kaplanis, Alexey A. Gritsenko, Matthias Minderer, Charles Blundell, Razvan Pascanu, Jovana Mitrovic

CoRR, 2024

2023

Neural Algorithmic Reasoning with Causal Regularisation.

Beatrice Bevilacqua, Kyriacos Nikiforou, Borja Ibarz, Ioana Bica, Michela Paganini, Charles Blundell, Jovana Mitrovic, Petar Velickovic

Proceedings of the International Conference on Machine Learning, 2023

SemPPL: Predicting Pseudo-Labels for Better Contrastive Representations.

Matko Bosnjak, Pierre Harvey Richemond, Nenad Tomasev, Florian Strub, Jacob C. Walker, Felix Hill, Lars Holger Buesing, Razvan Pascanu, Charles Blundell, Jovana Mitrovic

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Continually learning representations at scale.

Alexandre Galashov, Jovana Mitrovic, Dhruva Tirumala, Yee Whye Teh, Timothy Nguyen, Arslan Chaudhry, Razvan Pascanu

Proceedings of the Conference on Lifelong Learning Agents, 2023

2022

Pushing the limits of self-supervised ResNets: Can we outperform supervised learning without labels on ImageNet?

Nenad Tomasev, Ioana Bica, Brian McWilliams, Lars Buesing, Razvan Pascanu, Charles Blundell, Jovana Mitrovic

CoRR, 2022

CoBERL: Contrastive BERT for Reinforcement Learning.

Andrea Banino, Adrià Puigdomènech Badia, Jacob C. Walker, Tim Scholtes, Jovana Mitrovic, Charles Blundell

Proceedings of the Tenth International Conference on Learning Representations, 2022

2021

Encoders and Ensembles for Task-Free Continual Learning.

Murray Shanahan, Christos Kaplanis, Jovana Mitrovic

CoRR, 2021

Representation Learning via Invariant Causal Mechanisms.

Jovana Mitrovic, Brian McWilliams, Jacob C. Walker, Lars Holger Buesing, Charles Blundell

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

Can algorithms learn from babies? Exploring how infant learning can inform and inspire unsupervised learning algorithms.

Jelena Sucevic, Jovana Mitrovic

Proceedings of the 43th Annual Meeting of the Cognitive Science Society, 2021

2020

Amortized learning of neural causal representations.

Nan Rosemary Ke, Jane X. Wang, Jovana Mitrovic, Martin Szummer, Danilo J. Rezende

CoRR, 2020

Causally Correct Partial Models for Reinforcement Learning.

Danilo J. Rezende, Ivo Danihelka, George Papamakarios, Nan Rosemary Ke, Ray Jiang, Theophane Weber, Karol Gregor, Hamza Merzic, Fabio Viola, Jane Wang, Jovana Mitrovic, Frederic Besse, Ioannis Antonoglou, Lars Buesing

CoRR, 2020

Less can be more in contrastive learning.

Jovana Mitrovic, Brian McWilliams, Mélanie Rey

Proceedings of the "I Can't Believe It's Not Better!" at NeurIPS Workshops, 2020

2019

Causal Reasoning from Meta-reinforcement Learning.

Ishita Dasgupta, Jane X. Wang, Silvia Chiappa, Jovana Mitrovic, Pedro A. Ortega, David Raposo, Edward Hughes, Peter W. Battaglia, Matthew M. Botvinick, Zeb Kurth-Nelson

CoRR, 2019

2018

Hierarchical Adversarially Learned Inference.

Mohamed Ishmael Belghazi, Sai Rajeswar, Olivier Mastropietro, Negar Rostamzadeh, Jovana Mitrovic, Aaron C. Courville

CoRR, 2018

Causal Inference via Kernel Deviance Measures.

Jovana Mitrovic, Dino Sejdinovic, Yee Whye Teh

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

2017

Deep Kernel Machines via the Kernel Reparametrization Trick.

Jovana Mitrovic, Dino Sejdinovic, Yee Whye Teh

Proceedings of the 5th International Conference on Learning Representations, 2017

2016

DR-ABC: Approximate Bayesian Computation with Kernel-Based Distribution Regression.

Jovana Mitrovic, Dino Sejdinovic, Yee Whye Teh

Proceedings of the 33nd International Conference on Machine Learning, 2016