Jovana Mitrovic

Publication Activity (10 Years)

Years Active: 2016-2024
Publications (10 Years): 24

Top Topics

Max Margin Learning

Pitman Yor Process

Kernel Machines

Causal Inferences

Top Venues

Publications

Sahand Sharifzadeh, Christos Kaplanis, Shreya Pathak, Dharshan Kumaran, Anastasija Ilic, Jovana Mitrovic, Charles Blundell, Andrea Banino
: Boosting Visual-Language Models with Synthetic Captions and Image Embeddings. CoRR (2024)
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 (2024)
Beatrice Bevilacqua, Kyriacos Nikiforou, Borja Ibarz, Ioana Bica, Michela Paganini, Charles Blundell, Jovana Mitrovic, Petar Velickovic
Neural Algorithmic Reasoning with Causal Regularisation. ICML (2023)
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 (2023)
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)
Beatrice Bevilacqua, Kyriacos Nikiforou, Borja Ibarz, Ioana Bica, Michela Paganini, Charles Blundell, Jovana Mitrovic, Petar Velickovic
Neural Algorithmic Reasoning with Causal Regularisation. CoRR (2023)
Alexandre Galashov, Jovana Mitrovic, Dhruva Tirumala, Yee Whye Teh, Timothy Nguyen, Arslan Chaudhry, Razvan Pascanu
Continually learning representations at scale. CoLLAs (2023)
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 (2022)
Andrea Banino, Adrià Puigdomènech Badia, Jacob C. Walker, Tim Scholtes, Jovana Mitrovic, Charles Blundell
CoBERL: Contrastive BERT for Reinforcement Learning. ICLR (2022)
Jovana Mitrovic, Brian McWilliams, Jacob C. Walker, Lars Holger Buesing, Charles Blundell
Representation Learning via Invariant Causal Mechanisms. ICLR (2021)
Jelena Sucevic, Jovana Mitrovic
Can algorithms learn from babies? Exploring how infant learning can inform and inspire unsupervised learning algorithms. CogSci (2021)
Andrea Banino, Adrià Puigdomènech Badia, Jacob C. Walker, Tim Scholtes, Jovana Mitrovic, Charles Blundell
CoBERL: Contrastive BERT for Reinforcement Learning. CoRR (2021)
Murray Shanahan, Christos Kaplanis, Jovana Mitrovic
Encoders and Ensembles for Task-Free Continual Learning. CoRR (2021)
Nan Rosemary Ke, Jane X. Wang, Jovana Mitrovic, Martin Szummer, Danilo J. Rezende
Amortized learning of neural causal representations. CoRR (2020)
Jovana Mitrovic, Brian McWilliams, Mélanie Rey
Less can be more in contrastive learning. ICBINB@NeurIPS (2020)
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 (2020)
Jovana Mitrovic, Brian McWilliams, Jacob C. Walker, Lars Buesing, Charles Blundell
Representation Learning via Invariant Causal Mechanisms. CoRR (2020)
Ishita Dasgupta, Jane X. Wang, Silvia Chiappa, Jovana Mitrovic, Pedro A. Ortega, David Raposo, Edward Hughes, Peter W. Battaglia, Matthew Botvinick, Zeb Kurth-Nelson
Causal Reasoning from Meta-reinforcement Learning. CoRR (2019)
Jovana Mitrovic, Dino Sejdinovic, Yee Whye Teh
Causal Inference via Kernel Deviance Measures. NeurIPS (2018)
Mohamed Ishmael Belghazi, Sai Rajeswar, Olivier Mastropietro, Negar Rostamzadeh, Jovana Mitrovic, Aaron C. Courville
Hierarchical Adversarially Learned Inference. CoRR (2018)
Jovana Mitrovic, Dino Sejdinovic, Yee Whye Teh
Causal Inference via Kernel Deviance Measures. CoRR (2018)
Jovana Mitrovic, Dino Sejdinovic, Yee Whye Teh
Deep Kernel Machines via the Kernel Reparametrization Trick. ICLR (Workshop) (2017)
Jovana Mitrovic, Dino Sejdinovic, Yee Whye Teh
DR-ABC: Approximate Bayesian Computation with Kernel-Based Distribution Regression. ICML (2016)
Jovana Mitrovic, Dino Sejdinovic, Yee Whye Teh
DR-ABC: Approximate Bayesian Computation with Kernel-Based Distribution Regression. CoRR (2016)