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ORCIDJovana Mitrovic
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2020 – today
- 2024
[c11]Ioana Bica, Anastasija Ilic, Matthias Bauer, Goker Erdogan, Matko Bosnjak, Christos Kaplanis, Alexey A. Gritsenko, Matthias Minderer, Charles Blundell, Razvan Pascanu, Jovana Mitrovic:
Improving fine-grained understanding in image-text pre-training. ICML 2024- [i14]Ioana Bica, Anastasija Ilic, Matthias Bauer, Goker Erdogan, Matko Bosnjak, Christos Kaplanis, Alexey A. Gritsenko, Matthias Minderer, Charles Blundell, Razvan Pascanu, Jovana Mitrovic:
Improving fine-grained understanding in image-text pre-training. CoRR abs/2401.09865 (2024) - [i13]Sahand Sharifzadeh, Christos Kaplanis, Shreya Pathak, Dharshan Kumaran, Anastasija Ilic, Jovana Mitrovic, Charles Blundell, Andrea Banino:
Synth2: Boosting Visual-Language Models with Synthetic Captions and Image Embeddings. CoRR abs/2403.07750 (2024) - 2023
- [c10]Alexandre Galashov, Jovana Mitrovic, Dhruva Tirumala, Yee Whye Teh, Timothy Nguyen, Arslan Chaudhry, Razvan Pascanu:
Continually learning representations at scale. CoLLAs 2023: 534-547 - [c9]Matko Bosnjak, Pierre Harvey Richemond, Nenad Tomasev, Florian Strub, Jacob C. Walker, Felix Hill, Lars Holger Buesing, Razvan Pascanu, Charles Blundell, Jovana Mitrovic:
SemPPL: Predicting Pseudo-Labels for Better Contrastive Representations. ICLR 2023 - [c8]Beatrice Bevilacqua, Kyriacos Nikiforou, Borja Ibarz, Ioana Bica, Michela Paganini, Charles Blundell, Jovana Mitrovic, Petar Velickovic:
Neural Algorithmic Reasoning with Causal Regularisation. ICML 2023: 2272-2288 - [i12]Matko Bosnjak, Pierre H. Richemond, Nenad Tomasev, Florian Strub, Jacob C. Walker, Felix Hill, Lars Holger Buesing, Razvan Pascanu, Charles Blundell, Jovana Mitrovic:
SemPPL: Predicting pseudo-labels for better contrastive representations. CoRR abs/2301.05158 (2023) - [i11]Beatrice Bevilacqua, Kyriacos Nikiforou, Borja Ibarz, Ioana Bica, Michela Paganini, Charles Blundell, Jovana Mitrovic, Petar Velickovic:
Neural Algorithmic Reasoning with Causal Regularisation. CoRR abs/2302.10258 (2023) - 2022
- [c7]Andrea Banino, Adrià Puigdomènech Badia, Jacob C. Walker, Tim Scholtes, Jovana Mitrovic, Charles Blundell:
CoBERL: Contrastive BERT for Reinforcement Learning. ICLR 2022 - [i10]Nenad Tomasev, Ioana Bica, Brian McWilliams, Lars Buesing, Razvan Pascanu, Charles Blundell, Jovana Mitrovic:
Pushing the limits of self-supervised ResNets: Can we outperform supervised learning without labels on ImageNet? CoRR abs/2201.05119 (2022) - 2021
- [c6]Jelena Sucevic, Jovana Mitrovic:
Can algorithms learn from babies? Exploring how infant learning can inform and inspire unsupervised learning algorithms. CogSci 2021 - [c5]Jovana Mitrovic, Brian McWilliams, Jacob C. Walker, Lars Holger Buesing, Charles Blundell:
Representation Learning via Invariant Causal Mechanisms. ICLR 2021 - [i9]Murray Shanahan, Christos Kaplanis, Jovana Mitrovic:
Encoders and Ensembles for Task-Free Continual Learning. CoRR abs/2105.13327 (2021) - [i8]Andrea Banino, Adrià Puigdomènech Badia, Jacob C. Walker, Tim Scholtes, Jovana Mitrovic, Charles Blundell:
CoBERL: Contrastive BERT for Reinforcement Learning. CoRR abs/2107.05431 (2021) - 2020
- [c4]Jovana Mitrovic, Brian McWilliams, Mélanie Rey:
Less can be more in contrastive learning. ICBINB@NeurIPS 2020: 70-75 - [i7]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:
Causally Correct Partial Models for Reinforcement Learning. CoRR abs/2002.02836 (2020) - [i6]Nan Rosemary Ke, Jane X. Wang, Jovana Mitrovic, Martin Szummer, Danilo J. Rezende:
Amortized learning of neural causal representations. CoRR abs/2008.09301 (2020) - [i5]Jovana Mitrovic, Brian McWilliams, Jacob C. Walker, Lars Buesing, Charles Blundell:
Representation Learning via Invariant Causal Mechanisms. CoRR abs/2010.07922 (2020)
2010 – 2019
- 2019
- [i4]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:
Causal Reasoning from Meta-reinforcement Learning. CoRR abs/1901.08162 (2019) - 2018
- [c3]Jovana Mitrovic, Dino Sejdinovic, Yee Whye Teh:
Causal Inference via Kernel Deviance Measures. NeurIPS 2018: 6986-6994 - [i3]Mohamed Ishmael Belghazi, Sai Rajeswar, Olivier Mastropietro, Negar Rostamzadeh, Jovana Mitrovic, Aaron C. Courville:
Hierarchical Adversarially Learned Inference. CoRR abs/1802.01071 (2018) - [i2]Jovana Mitrovic, Dino Sejdinovic, Yee Whye Teh:
Causal Inference via Kernel Deviance Measures. CoRR abs/1804.04622 (2018) - 2017
- [c2]Jovana Mitrovic, Dino Sejdinovic, Yee Whye Teh:
Deep Kernel Machines via the Kernel Reparametrization Trick. ICLR (Workshop) 2017 - 2016
- [c1]Jovana Mitrovic, Dino Sejdinovic, Yee Whye Teh:
DR-ABC: Approximate Bayesian Computation with Kernel-Based Distribution Regression. ICML 2016: 1482-1491 - [i1]Jovana Mitrovic, Dino Sejdinovic, Yee Whye Teh:
DR-ABC: Approximate Bayesian Computation with Kernel-Based Distribution Regression. CoRR abs/1602.04805 (2016)
Coauthor Index
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